Online research in philosophy

The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on (...) the relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation. (shrink)

Several key areas in modeling the cardiovascular and respiratory control systems are reviewed and examples are given which reflect the research state of the art in these areas. Attention is given to the interrelated issues of data collection, experimental design, and model application including model development and analysis. Examples are given of current clinical problems which can be examined via modeling, and important issues related to model adaptation to the clinical setting.

The scientific methodology underlying model-building is critically investigated. The modeling views of Popper and Samuelson and their prototypes are critically examined in the light of the theme of the moral law of unity of knowledge and unity of the world-system configured by the meta-epistemology of organic unity of knowledge. Upon such critical examination of received methodology of model-building in economics, the extended perspective?namely of integrating the moral law derived from the divine roots as the meta-epistemology?is rigorously studied. (...) The example of the Islamic prerogative in interpreting the holistic world-system through model-building in economics is highlighted. A religio-philosophical approach is adopted to exemplify some approaches in Islamic model-building. An especial focus is placed here on grassroots types of financing and activities. The critique of these models within the existing Islamic scholarship is carried out. The result is new dimensions of macroeconomic analysis that emanate in a logical way from the meta-epistemological approach, and oppose the mainstream ideas, both in received and Islamic economic thinking as of now. (shrink)

Levelt et al. attempt to “model their theory” with WEAVER++. Modeling theories requires a model theory. The time is ripe for a methodology for building, testing, and evaluating computational models. We propose a tentative, five-step framework for tackling this problem, within which we discuss the potential strengths and weaknesses of Levelt et al.'s modeling approach.

Read argues that modeling cultural idea systems serves to make explicit the cultural rules through which "cultural idea systems" frame behaviors that are culturally meaningful. Because cultural rules are typically "invisible" to us, one of the anthropologists' tasks is to elicit these rules, make them explicit and then use them to build explanations for patterns in cultural phenomena. The main example of Read's approach to cultural idea systems is the formal modeling of kinship terminologies. I reconstruct Read's (...) class='Hi'>modeling strategy as comprising the following steps:From the way in which culture-bearers compute kin relations a data model is construed that makes explicit the cultural theory embedded in a kinship .. (shrink)

The Lotka–Volterra predator-prey-model is a widely known example of model-based science. Here we reexamine Vito Volterra’s and Umberto D’Ancona’s original publications on the model, and in particular their methodological reflections. On this basis we develop several ideas pertaining to the philosophical debate on the scientific practice of modeling. First, we show that Volterra and D’Ancona chose modeling because the problem in hand could not be approached by more direct methods such as causal inference. This suggests (...) a philosophically insightful motivation for choosing the strategy of modeling. Second, we show that the development of the model follows a trajectory from a “how possibly” to a “how actually” model. We discuss how and to what extent Volterra and D’Ancona were able to advance their model along that trajectory. It turns out they were unable to establish that their model was fully applicable to any system. Third, we consider another instance of model-based science: Darwin’s model of the origin and distribution of coral atolls in the Pacific Ocean. Darwin argued more successfully that his model faithfully represents the causal structure of the target system, and hence that it is a “how actually” model. (shrink)

This book models and simulates metaphysics by presenting the metaphysics of a model.

The credibility of digital computer simulations has always been a problem. Today, through the debate on verification and validation, it has become a key issue. I will review the existing theses on that question. I will show that, due to the role of epistemological beliefs in science, no general agreement can be found on this matter. Hence, the complexity of the construction of sciences must be acknowledged. I illustrate these claims with a recent historical example. Finally I temperate this diversity (...) by insisting on recent trends in environmental sciences and in industrial sciences. (shrink)

This paper evaluates Nancy Cartwright’s critique of economic models. Cartwright argues that economics fails to build relevant “nomological machines” able to isolate capacities. In this paper, I contend that many economic models are not used as nomological machines. I give some evidence for this claim and build on an inferential and pragmatic approach to economic modeling. Modeling in economics responds to peculiar inferential norms where a “good” model is essentially a model that enhances our knowledge about (...) possible worlds. As a consequence, models and experiments are very different knowledge-producing devices, at least in economics. (shrink)

Contemporary literature in philosophy of science has begun to emphasize the practice of modeling, which differs in important respects from other forms of representation and analysis central to standard philosophical accounts. This literature has stressed the constructed nature of models, their autonomy, and the utility of their high degrees of idealization. What this new literature about modeling lacks, however, is a comprehensive account of the models that figure in to the practice of modeling. This paper offers a (...) new account of both concrete and mathematical models, with special emphasis on the intentions of theorists, which are necessary for evaluating the model-world relationship during the practice of modeling. Although mathematical models form the basis of most of contemporary modeling, my discussion begins with more traditional, concrete models such as the San Francisco Bay model. (shrink)

Mathematical models are a well established tool in most natural sciences. Although models have been neglected by the philosophy of science for a long time, their epistemological status as a link between theory and reality is now fairly well understood. However, regarding the epistemological status of mathematical models in the social sciences, there still exists a considerable unclarity. In my paper I argue that this results from specific challenges that mathematical models and especially computer simulations face in the social sciences. (...) The most important difference between the social sciences and the natural sciences with respect to modeling is that in the social sciences powerful and well confirmed background theories (like Newtonian mechanics, quantum mechanics or the theory of relativity in physics) do not exist in the social sciences. Therefore, an epistemology of models that is formed on the role model of physics may not be appropriate for the social sciences. I discuss the challenges that modeling faces in the social sciences and point out their epistemological consequences. The most important consequences are that greater emphasis must be placed on empirical validation than on theoretical validation and that the relevance of purely theoretical simulations is strongly limited. (shrink)

The emphasis on models hasn’t completely eliminated laws from scientific discourse and philosophical discussion. Instead, I want to argue that much of physics lies beyond the strict domain of laws. I shall argue that in important cases the physics, or physical understanding, does not lie either in laws or in their properties, such as universality, consistency and symmetry. I shall argue that the domain of application commonly attributed to laws is too narrow. That is, laws can still play an important, (...) though peculiar, role outside their strict domain of validity. I shall argue also that, by way of a trade-off, while the actual domain of application of laws should be seen as much broader. At the same time, what I call ‘anomic’ representational elements reveal themselves as central to the descriptive and explanatory power of theories and model: boundary conditions, state descriptions, structures, constraints, limits and mechanisms. I conclude with a brief consideration of how my discussion has consequences for discussion of understanding, unification, approximation and dispositional properties. I focus on examples from physics, macroscopic and microscopic, phenomenological and fundametal: shock waves, propagation of cracks, symmetry breaking, and others. This law-eccentric kind of knowledge is central to both modeling the world and intervening in it. (shrink)

Subjective experience is transformed into objective reality for societal members through cultural idea systems that can be represented with theory and data models. A theory model shows relationships and their logical implications that structure a cultural idea system. A data model expresses patterning found in ethnographic observations regarding the behavioral implementation of cultural idea systems. An example of this duality for modeling cultural idea systems is illustrated with Arabic proverbs that structurally link friend and enemy as concepts (...) through a culturally defined computational system. Computational systems also generate new concepts, as will be illustrated through a theory model for the structure of a .. (shrink)

Scientific research is almost always conducted by communities of scientists of varying size and complexity. Such communities are effective, in part, because they divide their cognitive labor: not every scientist works on the same project. Philip Kitcher and Michael Strevens have pioneered efforts to understand this division of cognitive labor by proposing models of how scientists make decisions about which project to work on. For such models to be useful, they must be simple enough for us to understand their dynamics, (...) but faithful enough to reality that we can use them to analyze real scientific communities. To satisfy the first requirement, we must employ idealizations to simplify the model. The second requirement demands that these idealizations not be so extreme that we lose the ability to describe real-world phenomena. This paper investigates the status of the assumptions that Kitcher and Strevens make in their models, by first inquiring whether they are reasonable representations of reality, and then by checking the models’ robustness against weakenings of these assumptions. To do this, we first argue against the reality of the assumptions, and then develop a series of agent-based simulations to systematically test their effects on model outcomes. We find that the models are not robust against weakenings of these idealizations. In fact we find that under certain conditions, this can lead to the model predicting outcomes that are qualitatively opposite of the original model outcomes. (shrink)

In this paper, we try to shed light on the ontological puzzle pertaining to models and to contribute to a better understanding of what models are. Our suggestion is that models should be regarded as a specific kind of signs according to the sign theory put forward by Charles S. Peirce, and, more precisely, as icons, i.e. as signs which are characterized by a similarity relation between sign (model) and object (original). We argue for this (1) by analyzing from (...) a semiotic point of view the representational relation which is characteristic of models. We then corroborate our hypothesis (2) by discussing the conceptual differences between icons, i.e. models, and indexical and symbolic signs and (3) by putting forward a general classification of all icons into three functional subclasses (images, diagrams, and metaphors). Subsequently, we (4) integratively refine our results by resorting to two influential and, as can be shown, complementary philosophy of science approaches to models. This yields the following result: models are determined by a semiotic structure in which a subject intentionally uses an object, i.e. the model, as a sign for another object, i.e. the original, in the context of a chosen theory or language in order to attain a specific end by instituting a representational relation in which the syntactic structure of the model, i.e. its attributes and relations, represents by way of a mapping the properties of the original, which hence are regarded as similar in a relevant manner. (shrink)

In “Can Models of God Compete?”, J. R. Hustwit engages with fundamental questions regarding the epistemological foundations of modeling God. He argues that the approach of fallibilism best captures the criteria he employs to choose among different “models of God-modeling,” including one criterion that I call the Descriptive Criterion. I argue that Hustwit’s case for fallibilism should include both a stronger defense for the Descriptive Criterion and an explanation of the reasons that fallibilism does not run awry of (...) this criterion in virtue of its apparent inability to make sense of debates among models of God extant in religious communities. This paper was delivered during the APA Pacific 2007 Mini-Conference on Models of God. (shrink)

Experimental activity is traditionally identified with testing the empirical implications or numerical simulations of models against data. In critical reaction to the ‘tribunal view’ on experiments, this essay will show the constructive contribution of experimental activity to the processes of modeling and simulating. Based on the analysis of a case in fluid mechanics, it will focus specifically on two aspects. The first is the controversial specification of the conditions in which the data are to be obtained. The second is (...) conceptual clarification, with a redefinition of concepts central to the understanding of the phenomenon and the conditions of its occurrence. (shrink)

The descriptions and theoretical laws scientists write down when they model a system are often false of any real system. And yet we commonly talk as if there were objects that satisfy the scientists’ assumptions and as if we may learn about their properties. Many attempt to make sense of this by taking the scientists’ descriptions and theoretical laws to define abstract or fictional entities. In this paper, I propose an alternative account of theoretical modelling that draws upon (...) Kendall Walton’s ‘make-believe’ theory of representation in art. I argue that this account allows us to understand theoretical modelling without positing any object of which scientists’ modelling assumptions are true. (shrink)

Despite efforts from regulatory agencies (e.g. NIH, FDA), recent systematic reviews of randomised controlled trials (RCTs) show that top medical journals continue to publish trials without requiring authors to report details for readers to evaluate early stopping decisions carefully. This article presents a systematic way of modelling and simulating interim monitoring decisions of RCTs. By taking an approach that is both general and rigorous, the proposed framework models and evaluates early stopping decisions of RCTs based on a clear and (...) consistent set of criteria. The framework allows decision analysts to generate and quickly answer ‘what-if’ questions by simulating alternate trial scenarios. I illustrate the framework with a case study of an RCT that was stopped early due to harm. This was a trial of vitamin A supplement in relation to HIV transmission from mother-to-child through breastfeeding. (shrink)

Model organisms are central to contemporary biology and studies of embryogenesis in particular. Biologists utilize only a small number of species to experimentally elucidate the phenomena and mechanisms of development. Critics have questioned whether these experimental models are good representatives of their targets because of the inherent biases involved in their selection (e.g., rapid development and short generation time). A standard response is that the manipulative molecular techniques available for experimental analysis mitigate, if not counterbalance, this concern. But the (...) most powerful investigative techniques and molecular methods are applicable to single-celled organisms (‘microbes’). Why not use unicellular rather than multicellular model organisms, which are the standard for developmental biology? To claim that microbes are not good representatives takes us back to the original criticism leveled against model organisms. Using empirical case studies of microbes modeling ontogeny, we break out of this circle of reasoning by showing: (a) that the criterion of representation is more complex than earlier discussions have emphasized; and, (b) that different aspects of manipulability are comparable in importance to representation when deciding if a model organism is a good model. These aspects of manipulability harbor the prospect of enhancing representation. The result is a better understanding of how developmental biologists conceptualize research using experimental models and suggestions for underappreciated avenues of inquiry using microbes. More generally, it demonstrates how the practical aspects of experimental biology must be scrutinized in order to understand the associated scientific reasoning. (shrink)

This document discusses the status of research on detection and prevention of financial fraud undertaken as part of the IST European Commission funded FF POIROT (Financial Fraud Prevention Oriented Information Resources Using Ontology Technology) project. A first task has been the specification of the user requirements that define the functionality of the financial fraud ontology to be designed by the FF POIROT partners. It is claimed here that modeling fraudulent activity involves a mixture of law and facts as well (...) as inferences about facts present, facts presumed or facts missing. The purpose of this paper is to explain this abstract model and to specify the set of user requirements. (shrink)

In 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober’s (1993) critiques of Levins, and argue that his views on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary genetics. (...) Further, I argue that robustness analysis is a tool for, if not confirmation, then something near enough, in this discipline. (shrink)

Climate change presents us with a problem of intergenerational justice. While any costs associated with climate change mitigation measures will have to be borne by the world’s present generation, the main beneficiaries of mitigation measures will be future generations. This raises the question to what extent present generations have a responsibility to shoulder these costs. One influential approach for addressing this question is to appeal to neo-classical economic cost–benefit analyses and so-called economy-climate “integrated assessment models” to determine what course of (...) action a principle of intergenerational welfare maximization would require of us. I critically examine a range of problems for this approach. First, integrated assessment models face a problem of underdetermination and induction: They are very sensitive to a number of highly conjectural assumptions about economic responses to a temperature and climate regime, for which we have no empirical evidence. Second, they involve several simplifying assumptions which cannot be justified empirically. And third, some of the assumptions underlying the construction of economic models are intrinsically normative assumptions that reflect value judgments of the modeler. I conclude that, while integrated assessment models may play a useful role as “toy models,” their use as tools for policy optimization is highly problematic. (shrink)

In the last few decades the role played by models and modeling activities has become a central topic in the scientific enterprise. In particular, it has been highlighted both that the development of models constitutes a crucial step for understanding the world and that the developed models operate as mediators between theories and the world. Such perspective is exploited here to cope with the issue as to whether error-based and uncertainty-based modeling of measurement are incompatible, and thus alternative (...) with one another, as sometimes claimed nowadays. The crucial problem is whether assuming this standpoint implies definitely renouncing to maintain a role for truth and the related concepts, particularly accuracy, in measurement. It is argued here that the well known objections against true values in measurement, which would lead to refuse the concept of accuracy as non-operational, or to maintain it as only qualitative, derive from a not clear distinction between three distinct processes: the metrological characterization of measuring systems, their calibration, and finally measurement. Under the hypotheses that (1) the concept of true value is related to the model of a measurement process, (2) the concept of uncertainty is related to the connection between such model and the world, and (3) accuracy is a property of measuring systems (and not of measurement results) and uncertainty is a property of measurement results (and not of measuring systems), not only the compatibility but actually the conjoint need of error-based and uncertainty-based modeling emerges. (shrink)

Modeling a complex phenomena such as the mind presents tremendous computational complexity challenges. Modeling field theory (MFT) addresses these challenges in a non-traditional way. The main idea behind MFT is to match levels of uncertainty of the model (also, a problem or some theory) with levels of uncertainty of the evaluation criterion used to identify that model. When a model becomes more certain, then the evaluation criterion is adjusted dynamically to match that change to the (...) model. This process is called the Dynamic Logic of Phenomena (DLP) for model construction and it mimics processes of the mind and natural evolution. This paper provides a formal description of DLP by specifying its syntax, semantics, and reasoning system. We also outline links between DLP and other logical approaches. Computational complexity issues that motivate this work are presented using an example of polynomial models. (shrink)

The use of mathematical models to support decision making is proliferating in both the public and private sectors. Advances in computer technology and greater opportunities to learn the appropriate techniques are extending modeling capabilities to more and more people. As powerful decision aids, models can be both beneficial or harmful. At present, few safeguards exist to prevent model builders or users from deliberately, carelessly, or recklessly manipulating data to further their own ends. Perhaps more importantly, few people understand (...) or appreciate that harm can be caused when builders or users fail to recognize the values and assumptions on which a model is based or fail to take into account all the groups who would be affected by a model's results. This volume provides a setting for a dialogue about ethics and shows the need to continue and define a vocabulary for exploring ethical concerns. It will become increasingly important for model builders and users to have a clear and strong code of ethics to guide them in making the ethical decisions they surely will have to face. (shrink)

The nature of complex concepts has important implications for the computational modelling of the mind, as well as for the cognitive science of concepts. This paper outlines the way in which RVC – a Relational View of Concepts – accommodates a range of complex concepts, cases which have been argued to be non-compositional. RVC attempts to integrate a number of psychological, linguistic and psycholinguistic considerations with the situation-theoretic view that information-carrying relations hold only relative to background situations. The central (...) tenet of RVC is that the content of concepts varies systematically with perspective. The analysis of complex concepts indicates that compositionality too should be considered to be sensitive to perspective. Such a view accords with concepts and mental states being situated and the implications for theories of concepts and for computational models of the mind are discussed. (shrink)

It is argued that complexity is not attributable directly to systems or processes but rather to the descriptions of their `best' models, to reflect their difficulty. Thus it is relative to the modelling language and type of difficulty. This approach to complexity is situated in a model of modelling. Such an approach makes sense of a number of aspects of scientific modelling: complexity is not situated between order and disorder; noise can be explicated by approaches to (...) excess modelling error; and simplicity is not truth indicative but a useful heuristic when models are produced by a being with a tendency to elaborate in the face of error. (shrink)

In an instant classic paper (Lazebnik, in Cancer Cell 2(3); 2002 : 179–182) biologist Yuri Lazebnik deplores the poor effectiveness of the approach adopted by biologists to understand and “fix” biological systems. Lazebnik suggests that to remedy this state of things biologist should take inspiration from the approach used by engineers to design, understand, and troubleshoot technological systems. In the present paper I substantiate Lazebnik’s analysis by concretely showing how to apply the engineering approach to biological problems. I use an (...) actual example of electronic circuit troubleshooting to ground the thesis that, in engineering, the crucial phases of any non-trivial troubleshooting process are aimed at generating a mechanistic explanation of the functioning of the system, which makes extensive recourse to problem-driven qualitative reasoning possibly based on cognitive artifacts applied to systems that are known to have been designed for function . To show how to translate these findings into biological practice I consider a concrete example of biological model building and “troubleshooting”, aimed at the identification of a “fix” for the human immune system in presence of progressing cancer, autoimmune disease, and transplant rejection. The result is a novel immune system model—the danger model with regulatory cells— and new, original hypotheses concerning the development, prophylaxis, and therapy of these unwanted biological processes. Based on the manifest efficacy of the proposed approach, I suggest a refocusing of the activity of theoretical biologists along the engineering-inspired lines illustrated in the paper. (shrink)

A chief aim of the science of consciousness is to discover general principles that determine exactly which states of phenomenal consciousness occur in exactly which conditions. In this paper I argue that making progress towards the discovery of such principles requires developing a new regimented language for describing phenomenal states. This language should allow us to describe phenomenal states in a way that is commensurable with our descriptions of physical states. I suggest one way of doing this. My approach extends (...) and sharpens the language used in the scientific literature to describe phenomenal states. The end result is a representational language of consciousness without the metaphysical baggage of a representational theory of consciousness. (shrink)

Over the last decade, fully distributed models have become dominant in connectionist psychological modelling, whereas the virtues of localist models have been underestimated. This target article illustrates some of the benefits of localist modelling. Localist models are characterized by the presence of localist representations rather than the absence of distributed representations. A generalized localist model is proposed that exhibits many of the properties of fully distributed models. It can be applied to a number of problems that are (...) difficult for fully distributed models, and its applicability can be extended through comparisons with a number of classic mathematical models of behaviour. There are reasons why localist models have been underused, though these often misconstrue the localist position. In particular, many conclusions about connectionist representation, based on neuroscientific observation, can be called into question. There are still some problems inherent in the application of fully distributed systems and some inadequacies in proposed solutions to these problems. In the domain of psychological modelling, localist modelling is to be preferred. Key Words: choice; competition; connectionist modelling; consolidation; distributed; localist; neural networks; reaction-time. (shrink)

I argue that scientific explanation has a pragmatic dimension that is epistemically relevant. Philosophers with an objectivist approach to scientific explanation (e.g. Hempel, Trout) hold that the pragmatic aspects of explanation do not have any epistemic import. I argue against this view by focusing on the role of models in scientific explanation. Applying recent accounts of modelling (Cartwright, Morgan and Morrison) to a case-study of nineteenth-century physics, I analyse the pragmatic dimension of the process of model construction. I (...) highlight the crucial roles that conceptual tools, skills, and commitments play in this dimension, and show how they contribute to the epistemic aim of science. (shrink)

Linear structural equation models (SEMs) are widely used in sociology, econometrics, biology, and other sciences. A SEM (without free parameters) has two parts: a probability distribution (in the Normal case specified by a set of linear structural equations and a covariance matrix among the “error” or “disturbance” terms), and an associated path diagram corresponding to the causal relations among variables specified by the structural equations and the correlations among the error terms. It is often thought that the path diagram is (...) nothing more than a heuristic device for illustrating the assumptions of the model. However, in this paper, we will show how path diagrams can be used to solve a number of important problems in structural equation modelling. (shrink)

Modeling and simulation clearly have an upside. My discussion here will deal with the inevitable downside of modeling — the sort of things that can go wrong. It will set out a taxonomy for the pathology of models — a catalogue of the various ways in which model contrivance can go awry. In the course of that discussion, I also call on some of my past experience with models and their vulnerabilities.

The strategies of action employed by a human subject in order to perceive simple 2-D forms on the basis of tactile sensory feedback have been modelled by an explicit computer algorithm. The modelling process has been constrained and informed by the capacity of human subjects both to consciously describe their own strategies, and to apply explicit strategies; thus, the strategies effectively employed by the human subject have been influenced by the modelling process itself. On this basis, good qualitative (...) and semi-quantitative agreement has been achieved between the trajectories produced by a human subject, and the traces produced by a computer algorithm. The advantage of this reciprocal modelling option, besides facilitating agreement between the algorithm and the empirically observed trajectories, is that the theoretical model provides an explanation, and not just a description, of the active perception of the human subject. (shrink)

This paper examines creative strategies employed inscientific modelling. It is argued that being creativepresents not a discrete event, but rather an ongoingeffort consisting of many individual `creative acts''.These take place over extended periods of time andcan be carried out by different people, working ondifferent aspects of the same project. The example ofextended extragalactic radio sources shows that, inorder to model a complicated phenomenon in itsentirety, the modelling task is split up into smallerproblems that result in several sub-models. (...) This is away of using cognitive resources efficiently and in away which overcomes their limitations. Another aspectof modelling that requires creativity is theemployment of visualisation in order to reassemble,i.e. recreate the unity of, the various sub-models bymeans of visualisation. This illustrates how thecreative effort required to deal with the complexityof the complicated phenomenon of radio sources ischannelled in order to use cognitive resourcesefficiently and to stay within their capacity. (shrink)

Designing models of complex phenomena is a difficult task in engineering that can be tackled by composing a number of partial models to produce a global model of the phenomena. We propose to embed the partial models in software agents and to implement their composition as a cooperative negotiation between the agents. The resulting multiagent system provides a global model of a phenomenon. We applied this approach in modelling two complex physiological processes: the heart rate regulation and (...) the glucose-insulin metabolism. Beyond the effectiveness demonstrated in these two applications, the idea of using models associated to software agents to give reason of complex phenomena is in accordance with current tendencies in epistemology, where it is evident an increasing use of computational models for scientific explanation and analysis. Therefore, our approach has not only a practical, but also a theoretical significance: agents embedding models are a technology suitable both to representing and to investigating reality. (shrink)

In this paper we describe in some detail a formal computer model of inferential discourse based on a belief system. The key issue is that a logical model in a computer, based on rational sets, can usefully model a human situation based on irrational sets. The background of this work is explained elsewhere, as is the issue of rational and irrational sets (Billinge and Addis, in: Magnani and Dossena (eds.), Computing, philosophy and cognition, 2004; Stepney et al., (...) Journey: Non-classical philosophy—socially sensitive computing in journeys non-classical computation: A grand challenge for computing research, 2004). The model is based on the Belief System (Addis and Gooding, Proceedings of the AISB’99 Symposium on Scientific Creativity, 1999) and it provides a mechanism for choosing queries based on a range of belief. We explain how it provides a way to update the belief based on query results, thus modelling others’ experience by inference. We also demonstrate that for the same internal experience, different models can be built for different actors. (shrink)

Cardiovascular modelling has been a major research subject for the last decade. Different cardiac models have been developed at a cellular level as well as at the whole organ level. Most of these models are defined by a comprehensive cellular modelling using continuous formalisms or by a tissue-level modelling often based on discrete formalisms. Nevertheless, both views still suffer from difficulties that reduce their clinical applications: the first approach requires heavy computational resources while the second one is (...) not able to reproduce certain pathologies.This paper presents an original methodology trying to gather advantages from both approaches, by means of a hybrid model mixing discrete and continuous formalisms. This method has been applied to define a hybrid model of cardiac action potential propagation on a 2D grid of endocardial cells, combining cellular automata and a set of cells defined by the Beeler-Reuter model. For simulations under physiological and ischemic conditions, results show that the action potential propagation as well as electrogram reconstructions are consistent with clinical diagnosis. Finally, the advantage of the proposed approach is discussed within the frame of cardiac modelling and simulation. (shrink)

The perspective of modelling agents rather than using them for a specificed purpose entails a difference in approach. In particular an emphasis on veracity as opposed to efficiency. An approach using evolving populations of mental models is described that goes some way to meet these concerns. It is then argued that social intelligence is not merely intelligence plus interaction but should allow for individual relationships to develop between agents. This means that, at least, agents must be able to distinguish, (...) identify, model and address other agents, either individually or in groups. In other words that purely homogeneous interaction is insufficient. Two example models are described that illustrate these concerns, the second in detail where agents act and communicate socially, where this is determined by the evolution of their mental models. Finally some problems that arise in the interpretation of such simulations is discussed. (shrink)

This study examined how ethical case study content and the process for working through case material influenced training effectiveness. Specifically, the effects of behavioral modeling content and the use of forecasting prompt questions on knowledge acquisition and transfer were tested. Graduate students participating in a case-based ethics training course read a case where the main actor demonstrated key behaviors effectively (mastery model), some behaviors effectively and some ineffectively (mixed model), or no behaviors (no model). The students (...) then responded to forecasting or summarizing prompts. Results revealed a main effect for modeling content. Explicitly modeling key behaviors within a case improved constraint analyses, sensemaking, and decision ethicality on a transfer task. The mastery model using effective behaviors was most beneficial. Forecasting prompts resulted in better transfer performance when the main actor used a mix of ineffective and effective behaviors. Implications for designing ethics training programs are discussed. (shrink)

Stimulation of airway myocytes by contractile agents such as acetylcholine (ACh) activates a Ca2+-activated Cl– current (IClCa) which may play a key role in calcium homeostasis of airway myocytes and hence in airway reactivity. The aim of the present study was to model IClCa in airway smooth muscle cells using a computerised model previously designed for simulation of cardiac myocyte functioning. Modelling was based on a simple resistor-battery permeation model combined with multiple binding site activation by (...) calcium. In order to validate the model, a combination of equations, used to mimic [Ca2+]i response to ACh stimulation, were incorporated into the model. The results indicate that the model developed in this article accounts for experimental recordings and electrophysiological characteristics of this current in airway smooth muscle cells, with parameter values consistent with those calculated from experimental data. Such a model may thus be used to predict IClCa functioning, though additional experimental data from airway myocytes would be useful to more accurately determine some parameter values of the model. (shrink)

Accounts of the relation between theories and models in biology concentrate on mathematical models. In this paper I consider the dual role of models as representations of natural systems and as a material basis for theorizing. In order to explicate the dual role, I develop the concept of a remnant model, a material entity made from parts of the natural system(s) under study. I present a case study of an important but neglected naturalist, Joseph Grinnell, to illustrate the extent (...) to which mundane practices in a museum setting constitute theorizing. I speculate that historical and sociological analyses of institutions can play a specific role in the philosophical analysis of model-building strategies. (shrink)

This paper contrasts and compares strategies of model-building in condensed matter physics and biology, with respect to their alleged unequal susceptibility to trade-offs between different theoretical desiderata. It challenges the view, often expressed in the philosophical literature on trade-offs in population biology, that the existence of systematic trade-offs is a feature that is specific to biological models, since unlike physics, biology studies evolved systems that exhibit considerable natural variability. By contrast, I argue that the development of ever more sophisticated (...) experimental, theoretical, and computational methods in physics is beginning to erode this contrast, since condensed matter physics is now in a position to measure, describe, model, and manipulate sample-specific features of individual systems – for example at the mesoscopic level – in a way that accounts for their contingency and heterogeneity. Model-building in certain areas of physics thus turns out to be more akin to modeling in biology than has been supposed and, indeed, has traditionally been the case. (shrink)

A serious crisis is identified in theories of neurocomputation, marked by a persistent disparity between the phenomenological or experiential account of visual perception and the neurophysiological level of description of the visual system. In particular, conventional concepts of neural processing offer no explanation for the holistic global aspects of perception identified by Gestalt theory. The problem is paradigmatic and can be traced to contemporary concepts of the functional role of the neural cell, known as the Neuron Doctrine. In the absence (...) of an alternative neurophysiologically plausible model, I propose a perceptual modeling approach, to model the percept as experienced subjectively, rather than modeling the objective neurophysiological state of the visual system that supposedly subserves that experience. A Gestalt Bubble model is presented to demonstrate how the elusive Gestalt principles of emergence, reification, and invariance can be expressed in a quantitative model of the subjective experience of visual consciousness. That model in turn reveals a unique computational strategy underlying visual processing, which is unlike any algorithm devised by man, and certainly unlike the atomistic feed-forward model of neurocomputation offered by the Neuron Doctrine paradigm. The perceptual modeling approach reveals the primary function of perception as that of generating a fully spatial virtual-reality replica of the external world in an internal representation. The common objections to this picture-in-the-head concept of perceptual representation are shown to be ill founded. Key Words: brain-anchored; Cartesian theatre; consciousness; emergence; extrinsic constraints; filling-in; Gestalt; homunculus; indirect realism; intrinsic constraints; invariance; isomorphism; multistability; objective phenomenology; perceptual modeling; perspective; phenomenology; psychophysical parallelism; psychophysical postulate; qualia; reification; representationalism; structural coherence. (shrink)

The story of the fall and rise of Zahavi’s handicap principle is one of a battle between models. Early attempts at formal modeling produced negative results and, unsurprisingly, scepticism about the principle. A major change came in 1990 with Grafen’s production of coherent models of a handicap mechanism of honest signalling. This paper’s first claim is that acceptance of the principle, and its dissemination into other disciplines, has been driven principally by that, and subsequent modeling, rather than by (...) empirical results. Secondly, there is a vast literature on biological signalling but few studies that make all of the observations necessary to diagnose the handicap mechanism. My final claim is that many of the applications of costly signalling theory in other disciplines are conceptually confused. Misinterpretations of what is meant by costly signalling are common. Demonstrating that a signal is costly is insufficient and is not always necessary in order to prove that, and explain why, a signal is honest. In addition to the biological modelling of signals, there is an economic literature on the same subject. The two run in parallel in the sense that they have had little mutual interaction. Additionally, it is the biological modelling that has been picked up, and often misapplied, by other disciplines. (shrink)

The prediction of protein–protein interactions based on independently obtained structural information for each interacting partner remains an important challenge in computational chemistry. Procedures where hypothetical interaction models (or decoys) are generated, then ranked using a biochemically relevant scoring function have been garnering interest as an avenue for addressing such challenges. The program PatchDock has been shown to produce reasonable decoys for modeling the association between pig alpha-amylase and the VH-domains of camelide antibody raised against it. We designed a biochemically (...) relevant method by which PatchDock decoys could be ranked in order to separate near-native structures from false positives. Several thousand steps of energy minimization were used to simulate induced fit within the otherwise rigid decoys and to rank them. We applied a partial free energy function to rank each of the binding modes, improving discrimination between near-native structures and false positives. Sorting decoys according to strain energy increased the proportion of near-native decoys near the bottom of the ranked list. Additionally, we propose a novel method which utilizes regression analysis for the selection of minimization convergence criteria and provides approximation of the partial free energy function as the number of algorithmic steps approaches infinity. (shrink)

The paper deals with an intellectual and historical approach to the changing meanings of the term “model” in life sciences. The author 1st tries to understand how modeling has gradually spread over life sciences then he particularly focus on the birth of mathematical modeling in this field. This quite new practice offers new insights on the old debate concerning the mathematization of life sciences. Nowadays, through computers, mathematics not only analyze or quantify but model things: what (...) does it mean? The question turns out to be dramatic as far as digital simulation is concerned. That is the reason why he choosed to study a particular case: the history of the individual plant mathematical modeling. On this case, one may discern various epistemological standpoints that caused various reactions to the emergence of computer simulation, from the 50s to the 90s. The author shows that philosophical views often play a role in the history of sciences, especially in the choice of supposed proper mathematical formalisms. This will indicate that contemporary discourses tend to echo each other. That is the reason why he feels authorized to address the Foucault’s concept—épistémè—to denote these convergences between the scientific and the philosophical discourses. Finally, it is suggested that this épistémè gradually is changing because one can currently observe the emergence of a “graphical” thought through these simulation experiments, which tends to replace a more functionalist thought. (shrink)

As brightly shown by Mainzer [24], the science of complexity has many distinct origins in many disciplines. Those various origins has led to “an interdisciplinary methodology to explain the emergence of certain macroscopic phenomena via the nonlinear interactions of microscopic elements” (ibid.). This paper suggests that the parallel and strong expansion of modeling and simulation - especially after the Second World War and the subsequent development of computers - is a rationale which also can be counted as an explanation (...) of this emergence. With the benefit of hindsight, one can find three periods in the methodologies of modeling in the empirical sciences: 1st the simple modeling of the simple, 2nd the simple modeling of the complex, 3rd the complex modeling and simulation of the complex. Our main thesis is that the current spreading (since the 90’s) of complex computer simulations of systems of models (where a simulation is no more a step by step calculus of a unique logico-mathematical model) is another promising dimension of the science of complexity. Following this claim, we propose to distinguish three different types of computer simulations in the context of complex systems’ modeling. Finally, we show that these types of simulations lead to three different types of weak emergence, too. (shrink)

If chemistry is to be taught successfully, teachers must have a good subject matter knowledge (SK) of the ideas with which they are dealing, the nature of this falling within the orbit of philosophy of chemistry. They must also have a good pedagogic content knowledge (PCK), the ability to communicate SK to students, the nature of this falling within the philosophy and psychology of chemical education. Taking the case of models and modelling, important themes in the philosophy of chemistry, (...) an interview-based study was conducted into the SK and PCK of a sample of teachers in Brazil. This paper focuses on the results of the university chemistry teacher sub-sample in that enquiry, analyses their SK and PCK, and speculates on the implications of this for the education of school teachers. Finally, it suggests approaches to the professional development of university chemistry teachers that place an emphasis on the philosophy of chemistry. (shrink)

Webb has articulated a clear, multi-dimensional framework for discussing simulation models and modelling strategies. This framework will likely co-evolve with modelling. As such, it will be important to continue to clarify these dimensions and perhaps add to them. I discuss the dimension of generality and suggest that a dimension of integrativeness may also be needed.

In his 1966 paper "The Strategy of model-building in Population Biology", Richard Levins argues that no single model in population biology can be maximally realistic, precise and general at the same time. This is because these desirable model properties trade-off against one another. Recently, philosophers have developed Levins' claims, arguing that trade-offs between these desiderata are generated by practical limitations on scientists, or due to formal aspects of models and how they represent the world. However this project (...) is not complete. The trade-offs discussed by Levins had a noticeable effect on modelling in population biology, but not on other sciences. This raises questions regarding why such a difference holds. I claim that in order to explain this finding, we must pay due attention to the properties of the systems, or targets modelled by the different branches of science. (shrink)

The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical sciences, a rigorous set of theories is a hierarchy of descriptions/explanations, in which causal relationships among entities at a (...) high level can be reduced to causal relationships among simpler entities at a more detailed level. We argue that a similar hierarchy makes possible an equally productive approach toward cognitive modeling. The levels of models that we conceive in relation to cognition include, at the highest level, sociological/anthropological models of collective human behavior, behavioral models of individual performance, cognitive models involving detailed mechanisms, representations, and processes, as well as biological/physiological models of neural circuits, brain regions, and other detailed biological processes. (shrink)

This work develops an epistemology of measurement, that is, an account of the conditions under which measurement and standardization methods produce knowledge as well as the nature, scope, and limits of this knowledge. I focus on three questions: (i) how is it possible to tell whether an instrument measures the quantity it is intended to? (ii) what do claims to measurement accuracy amount to, and how might such claims be justified? (iii) when is disagreement among instruments a sign of error, (...) and when does it imply that instruments measure different quantities? Based on a series of case studies conducted in collaboration with the US National Institute of Standards and Technology (NIST), I argue for a model-based approach to the epistemology of physical measurement. To measure a physical quantity, I argue, is to estimate the value of a parameter in an idealized model of a physical process. Such estimation involves inference from the final state (‘indication’) of a process to the value range of a parameter (‘outcome’) in light of theoretical and statistical assumptions. Contrary to contemporary philosophical views, measurement outcomes cannot be obtained by mapping the structure of indications. Instead, measurement outcomes as well as claims to accuracy, error and quantity individuation can only be adjudicated relative to a choice of idealized modelling assumptions. (shrink)

The debate between the Mendelians and the (largely Darwinian) biometricians has been referred to by R. A. Fisher as ‘one of the most needless controversies in the history of science’ and by David Hull as ‘an explicable embarrassment’. The literature on this topic consists mainly of explaining why the controversy occurred and what factors prevented it from being resolved. Regrettably, little or no mention is made of the issues that figured in its resolution. This paper deals with the latter topic (...) and in doing so reorients the focus of the debate as one between Karl Pearson and R. A. Fisher rather than between the biometricians and the Mendelians. One reason for this reorientation is that Pearson's own work in 1904 and 1909 suggested that Mendelism and biometry could, to some extent, be made compatible, yet he remained steadfast in his rejection of Mendelism. The interesting question then is why Fisher, who was also a proponent of biometric methods, was able to synthesise the two traditions in a way that Pearson either could not or would not. My answer to this question involves an analysis of the ways in which different kinds of assumptions were used in modelling Mendelian populations. I argue that it is these assumptions, which lay behind the statistical techniques of Pearson and Fisher, that can be isolated as the source of Pearson's rejection of Mendelism and Fisher's success in the synthesis. (shrink)

This paper introduces DEMO, a Dynamic Epistemic Modelling tool. DEMO allows modelling epistemic updates, graphical display of update results, graphical display of action models, formula evaluation in epistemic models, translation of dynamic epistemic formulas to PDL formulas, and so on. The paper implements the reduction of dynamic epistemic logic [16, 2, 3, 1] to PDL given in [12]. The reduction of dynamic epistemic logic to automata PDL from [24] is also discussed and implemented. Epistemic models are minimized under (...) bisimulation, and update action models are minimized under action emulation (the appropriate structural notion for having the same update effect, cf. [13]). The paper is an exemplar of tool building for epistemic update logic. It contains the full code of an implementation in Haskell [22], in ‘literate programming’ style [23], of DEMO. (shrink)

This paper describes the processes of cognitive modeling and representation of human expertise for developing an ontology and knowledge base of an expert system. An ontology is an organization and classification of knowledge. Ontological engineering in artificial intelligence (AI) has the practical goal of constructing frameworks for knowledge that allow computational systems to tackle knowledge-intensive problems and supports knowledge sharing and reuse. Ontological engineering is also a process that facilitates construction of the knowledge base of an intelligent system, which (...) can be defined as a computer program that can duplicate problem-solving capabilities of human experts in specific areas. This paper presents the processes of knowledge acquisition, analysis, and representation, which laid the basis for ontology construction. In this case, the processes are applied in ontological engineering for construction of an expert system in the domain of monitoring of a petroleum production and separation facility. The acquired knowledge was also formally represented in two knowledge acquisition tools. (shrink)

The SDML programming language which is optimized for modelling multi-agent interaction within articulated social structures such as organizations is described with several examples of its functionality. SDML is a strictly declarative modelling language which has object-oriented features and corresponds to a fragment of strongly grounded autoepistemic logic. The virtues of SDML include the ease of building complex models and the facility for representing agents flexibly as models of cognition as well as modularity and code reusability.

In this paper I argue that to explain and resolve some kinds of disagreement we need to go beyond what logic alone can provide. In particular, following Perelman, I argue that we need to consider how arguments are ascribed different strengths by different audiences, according to how accepting these arguments promotes values favoured by the audience to which they are addressed. I show how we can extend the standard framework for modelling argumentation systems to allow different audiences to be (...) represented. I also show how this formalism can explain how some disputes can be resolved while in others the parties can only agree to differ. I illustrate this by consideration of a legal example. Finally, I make some suggestions as to where these values come from, and how they can be used to explain differences across jurisdictions, and changes in views over time. (shrink)

This bibliographical review of the modelling of the mitotic apparatus covers a period of one hundred and twenty years, from the discovery of the bipolar mitotic spindle up to the present day. Without attempting to be fully comprehensive, it will describe the evolution of the main ideas that have left their mark on a century of experimental and theoretical research. Fol and Bütschli's first writings date back to 1873, at a time when Schleiden and Schwann's cell theory was rapidly (...) gaining ground throughout Germany. Both mitosis and chromosomes were to be discovered within the space of thirty years, along with the two key events in the animal and plant reproductive cycle, namely fecondation and meiosis. The mitotic pole, a term still in use to this day, was employed to describe a morphological fact which was noted as early as 1876, namely that the lines and the dots of the karyokinetic figure, with its spindle and asters, looks remarkably like the lines of force around a bar magnet. This was to lead to models designed to explain the movements of chromosomes which take place when the cell nucleus appears to cease to exist as an organelle during mitosis. The nature of those mechanisms and the origin of the forces behind the chromosomes' ordered movements were central to the debate. Auguste Prenant, in a remarkable bibliographical synthesis published in 1910, summed up the opposing viewpoints of the vitalists, on the one hand, who favoured the theory of contractility or extensility in spindle fibres, and of those who believed in models based on physical phenomena, on the other. The latter subdivided into two groups: some, like Bütschli, Rhumbler or Leduc, referred to diffusion, osmosis and superficial tension, whilst the others, led by Gallardo and Hartog, focussed on the laws of electromagnetism. Lillie, Kuwada and Darlington followed up this line of research. The mid-20th century was a major turning point. Most of the modelling mentioned above was criticized and fell into disuse after disappearing from research publications and textbooks.This marked the onset of a new era, as electron microscopes made possible the materialization and detailed study of the macromolecular elements of the fibres, filaments and microtubules of the cytoskeleton. The successive phases of (a) de Harven and Bernhard's 1956 discovery of the centriole's ultrastructure, (b) its identification with the basal body of the cilia and flagella, confirming the theory set out by Henneguy and von Lenhossek (1898–99), (c) the universal presence of microtubules in animal, vegetal and eukaryotic protist cells, (d) the polymerization-depolymerization induced reversible transformations of the tubulin pool in mitosing cells (Inoue, 1960), (e) ultrastructural comparative studies of the mitotic apparatus of eukaryotes illustrating the Pickett-Heaps integrating concept of the MTOC (microtubule-organizing centre), (f) the possibility ofin vitro experiments on mtocs or on microtubules, brings us upon the present day, which has seen the focus placed on the concept of motor-proteins (kinesin, dynein) and on cell cycle models. The latter are based on a close coincidence between the observable modifications of the mitotic apparatus and the periodic variations in intracellular concentrations of calcium or of certain enzymes (cyclins, Cdc2) during the main transitions of the cell cycle. (shrink)

The theoretical framework adopted in the exact sciences, for constructing and testing deterministic theories on the one hand, and modelling and analysis of observed phenomena on the other, is often implicitly assumed to be that of structural stability. In view of recent developments in nonlinear dynamics, it is argued here that in general it may not be possible to assume strict determinism and structural stability simultaneously; either strict determinism holds, in which case the fragility framework may turn out to (...) be the appropriate framework for the study of certain phenomena in the exact sciences, or ‘structural stability’ is restored at the expense of introducing stochasticity. In this sense a certain degree of indeterminacy may be unavoidable even at the classical level. (shrink)

Although many philosophers of science have recognized the importance of modeling in contemporary science, relatively little work has been done in developing a general account of models. The most widely accepted account, put forth by advocates of the semantic conception of theories, misleadingly identifies scientific models with the models of mathematical logic. I present an alternative theory of scientific models in which models are defined by their representational relation to a physical system. I explore in some detail a particular (...) sort of model called a ‘mechanical model’ I illustrate the applicability of my approach by applying it to a problem in contemporary speech perception research. The model of models is used to analyze how competing models of the mechanisms of vowel normalization are constructed, tested, and revised. (shrink)

Against the tradition, which has considered measurement able to produce pure data on physical systems, the unavoidable role played by the modeling activity in measurement is increasingly acknowledged, particularly with respect to the evaluation of measurement uncertainty. This paper characterizes measurement as a knowledge-based process and proposes a framework to understand the function of models in measurement and to systematically analyze their influence in the production of measurement results and their interpretation. To this aim, a general model of (...) measurement is sketched, which gives the context to highlight the unavoidable, although sometimes implicit, presence of models in measurement and, finally, to propose some remarks on the relations between models and measurement uncertainty, complementarily classified as due to the idealization implied in the models and their realization in the experimental setup. (shrink)

The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the core of (...) the FMSA is similar in both contexts: notions of “levels of system specifi cation”, “behavior of models”, “simulator”and “endomorphic agents” can be partially translated in the terms linked to the “denotational hierarchy” (DH) and recently introduced in a multi-level centered epistemology of M&S. Second, we suggest considering the question of “credibility” of agent M&S in social sciences when we do not try to emulate but only to simulate target systems. Whereas a stringent and standardized treatment of the heterogeneous internal relations (in the DH) between systems of formalisms is the key problem and the essential challenge in the scope of Agent M&S driven engineering, it is urgent too to address the problem of the external relations (and of the external validity, hence of the epistemic power and credibility) of such levels of formalisms in the specific domains of agent M&S in social sciences, especially when we intend to introduce the concepts of activity tracking. (shrink)

Computational modeling of the brain holds great promise as a bridge from brain to behavior. To fulfill this promise, however, it is not enough for models to be 'biologically plausible': models must be structurally accurate. Here, we analyze what this entails for so-called psychobiological models, models that address behavior as well as brain function in some detail. Structural accuracy may be supported by (1) a model's a priori plausibility, which comes from a reliance on evidence-based assumptions, (2) fitting (...) existing data, and (3) the derivation of new predictions. All three sources of support require modelers to be explicit about the ontology of the model, and require the existence of data constraining the modeling. For situations in which such data are only sparsely available, we suggest a new approach. If several models are constructed that together form a hierarchy of models, higher-level models can be constrained by lower-level models, and low-level models can be constrained by behavioral features of the higher-level models. Modeling the same substrate at different levels of representation, as proposed here, thus has benefits that exceed the merits of each model in the hierarchy on its own. (shrink)

One approach to understanding model-based reasoning in science is to examine how it develops during infancy, childhood, and adolescence. The way in which thinking changes sometimes provides clues to its nature. This paper examines cognitive developmental aspects of modeling practices and discusses how a developmental perspective can enrich the study of model-based scientific reasoning in adults. The paper begins with issues concerning developmental change, followed by a model of model-based reasoning. The rest of the paper (...) describes how several key concepts from recent developmental work could contribute to current work on model-based reasoning. Specifically, developmental research shows that (a) social processes are involved in model-based reasoning and scientific discovery, (b) the development of a theory of mind contributes to the development of scientific reasoning, (c) changes in scientific reasoning are characterized by cognitive variability, and (d) microgenetic methods could clarify conceptual change during model-based reasoning. (shrink)

The interactive-alignment model of dialogue provides an account of dialogue at the level of explanation normally associated with cognitive psychology. We develop our claim that interlocutors align their mental models via priming at many levels of linguistic representation, explicate our notion of automaticity, defend the minimal role of “other modeling,” and discuss the relationship between monologue and dialogue. The account can be applied to social and developmental psychology, and would benefit from computational modeling.

I investigate how theoretical assumptions, pertinent to different perspectives and operative during the modeling process, are central in determining how nature is actually taken to be. I explore two different models by Michael Turelli and Steve Frank of the evolution of parasite-mediated cytoplasmic incompatility, guided, respectively, by Fisherian and Wrightian perspectives. Since the two models can be shown to be commensurable both with respect to mathematics and data, I argue that the differences between them in the (1) mathematical presentation (...) of the models, (2) explanations, and (3) objectified ontologies stem neither from differences in mathematical method nor the employed data, but from differences in the theoretical assumptions, especially regarding ontology, already present in the respective perspectives. I use my "set up, mathematically manipulate, explain, and objectify" (SMEO) account of the modeling process to track the model-mediated imposition of theoretical assumptions. I conclude with a discussion of the general implications of my analysis of these models for the controversy between Fisherian and Wrightian perspectives. (shrink)

This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ (...) article is concerned, at its core, with justifying the use of multiple, idealized models in population biology. (shrink)

Carl Gustav Hempel was one of the most influential figures in the development of “scientific philosophy” in the twentieth century, particularly in the English-speaking world. While he made a variety of contributions to the philosophy of science, he is perhaps most remembered for his careful formulation and detailed elaboration of the “Covering Law model” for scientific explanation. In this essay I consider why the CL model was, and still is, so influential, in spite of the fact that it (...) has been subjected to many criticisms and is usually seen as superseded by alternative models. Answering this question involves a reexamination of Hempel’s relationship to other influential “scientific philosophers”, especially Rudolf Carnap. It also sheds new light on issues concerning the notions of analysis, explication, and modeling that remain relevant today. (shrink)

The paper suggests a way of modeling belief changes within the tradition of formal belief revision theories. The present model extends the scope of traditional proposals, such as AGM, so as to take care of “structural belief changes” – a type of radical shifts that is best illustrated with, but not limited to, instances of scientific discovery; we obtain AGM expansions and contractions as limiting cases. The representation strategy relies on a non-standard use of a semantic machinery. More (...) precisely, the model seeks to correlate knowledge states with interpretations of a given formal language L, in such a way that the epistemic state of an agent at a given time gives rise to a picture of how things could be, if there weren’t anything else to know. Interpretations of L proceed along supervaluational ideas; hence, the model as a whole can be seen as a particular application of supervaluational semantics to epistemic matters. (shrink)

In today’s society, models of God are challenged to account for more than the postmodern context in which Western Christianity finds itself; they should also consider the reality of religious pluralism. Non-monotheistic religions present a particular challenge to Western theological and philosophical God-modeling because they require a model of Gods. This paper uses an African traditional religion as a case study to problematize the effects of monotheism on philosophical models of God. The desire to uphold the image of (...) a singular God tends to invalidate religious experiences that deviate from a given scientifically-verifiable norm. It also mischaracterizes the concept of divinity in religions that maintain divine multiplicity. That is, scholars of African traditional religions affirm that polytheism is not an accurate naming of their traditions; rather these religions affirm a community of gods. I propose a Whiteheadian process model that describes a community of gods that has active interaction with the temporal world. Such a model not only broadens conversations of religious pluralism for Western-trained religious scholars, but also acknowledges the Western context in which many practitioners of African traditional religions live. (shrink)

The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic (...) and sub-symbolic information processing levels. Present account of models of computation highlights several topics of importance for the development of new understanding of computing and its role: natural computation and the relationship between the model and physical implementation, interactivity as fundamental for computational modelling of concurrent information processing systems such as living organisms and their networks, and the new developments in logic needed to support this generalized framework. Computing understood as information processing is closely related to natural sciences; it helps us recognize connections between sciences, and provides a unified approach for modeling and simulating of both living and non-living systems. (shrink)

Robert Merton's essays on theories of the middle range and his essays on functional explanation and the structural approach are among the most influential in the history of sociology. But their import is a puzzle. He explicitly allied himself with some of the most extreme scientistic formalists and contributed to and endorsed the Columbia model of theory construction. But Merton never responded to criticisms by Ernest Nagel of his arguments or acknowledged the rivalry between Lazarsfeld and Herbert Simon, rarely (...) cited the philosophical and methodological literature, and responded to critics with ambiguous concessions, leaving the Mertonian legacy profoundly ambiguous. Key Words: Robert Merton • Paul Lazarsfeld • theory construction • middle range theory • causal modeling • Émile Durkheim. (shrink)

The psycholinguistic literature has identified two syntactic adaptation effects in language production: rapidly decaying short-term priming and long-lasting adaptation. To explain both effects, we present an ACT-R model of syntactic priming based on a wide-coverage, lexicalized syntactic theory that explains priming as facilitation of lexical access. In this model, two well-established ACT-R mechanisms, base-level learning and spreading activation, account for long-term adaptation and short-term priming, respectively. Our model simulates incremental language production and in a series of (...) class='Hi'>modeling studies, we show that it accounts for (a) the inverse frequency interaction; (b) the absence of a decay in long-term priming; and (c) the cumulativity of long-term adaptation. The model also explains the lexical boost effect and the fact that it only applies to short-term priming. We also present corpus data that verify a prediction of the model, that is, that the lexical boost affects all lexical material, rather than just heads. (shrink)

The book Model-Based Reasoning in Scientific Discovery, aims to explain how specific modeling practices employed by scientists are productive methods of ...

(Total word count 2,647) I. Introduction. Given the work of Robert MacArthur and his followers, some skeptical ecologists charge that theoretical modeling building has gone evidentially unconstrained. That is, models are often constructed which resist empirical testing. In this essay, I argue that “bottle experiments” do provide model building with important evidential constraints using an example of chaos producing models that have been tested against the dynamics of flour beetle populations. Critics reply however that this and other bottle (...) experiments are importantly unlike and irrelevant to non-manipulated systems in nature. I provide two possible responses to this view. Finally, I provide a practical suggestion for how to move the debate forward. (shrink)

A values-centered leadership model comprised of leader stakeholder and economic values, follower values congruence, and responsible leadership outcomes was tested using data from 122 organizational leaders and 458 of their direct reports. Alleviating same-source bias concerns in leadership survey research, follower ratings of leadership style and follower ratings of values congruence and responsible leadership outcomes were collected from separate sources via the split-sample methodology. Results of structural equation modeling analyses demonstrated that leader stakeholder values predicted transformational leadership, whereas (...) leader economic values were associated with transactional leadership. Follower values congruence was strongly associated with transformational leadership, unrelated to transactional leadership, and partially mediated the relationships between transformational leadership and both follower organizational citizenship behaviors and follower beliefs in the stakeholder view of corporate social responsibility. Implications for responsible leadership and transformational leadership theory, practice, and future research are discussed. (shrink)

Despite a strong sensitization to the corruption problem and a large body of interdisciplinary research, scientists have only rarely investigated which motivational, volitional, emotional, and cognitive components make decision makers in companies act corruptly. Thus, we examined how their interrelation leads to corruption by proposing an action model. We tested the model using a business simulation game with students as participants. Results of the PLS structural equation modeling showed that both an attitude and subjective norm favoring corruption (...) led to a desire to act corruptly. Given high perceived behavioral control, this desire was transformed into an intention that finally resulted in corrupt action. Components related to general private and professional goals did not allow for any prediction. Based on these results, we discuss preventative measures and methods for combating intra- and inter-organizational corruption. (shrink)

In this paper, we study the performance of baseline hidden Markov model (HMM) for segmentation of speech signals. It is applied on single-speaker segmentation task, using Hindi speech database. The automatic phoneme segmentation framework evolved imitates the human phoneme segmentation process. A set of 44 Hindi phonemes were chosen for the segmentation experiment, wherein we used continuous density hidden Markov model (CDHMM) with a mixture of Gaussian distribution. The left-to-right topology with no skip states has been selected as (...) it is effective in speech recognition due to its consistency with the natural way of articulating the spoken words. This system accepts speech utterances along with their orthographic “transcriptions” and generates segmentation information of the speech. This corpus was used to develop context-independent hidden Markov models (HMMs) for each of the Hindi phonemes. The system was trained using numerous sentences that are relevant to provide information to the passengers of the Metro Rail. The system was validated against a few manually segmented speech utterances. The evaluation of the experiments shows that the best performance is obtained by using a combination of two Gaussians mixtures and five HMM states. A category-wise phoneme error analysis has been performed, and the performance of the phonetic segmentation has been reported. The modeling of HMMs has been implemented using Microsoft Visual Studio 2005 (C++), and the system is designed to work on Windows operating system. The goal of this study is automatic segmentation of speech at phonetic level. (shrink)

This paper describes a decision model for an autonomous agent that provides an inhabitant with comfort based on information network technologies that connect home electric appliances with household equipment. The inhabitant enjoys the benefit of comfort, while he pays the cost for keeping that comfort. The autonomous agent should decide and control household equipment considering that cost from the inhabitant’s viewpoint. Thus, we utilized a representation scheme called an “influence diagram” that enabled us to model the decision-making process (...) of the agent from the inhabitant’s point of view. First, decision modeling using the influence diagram is presented via an example. The presented model consists of three information-processing modules: a module for estimating the situation of an inhabitant based on information from home networks, a module for evaluating comfort of the inhabitant, and a module for making decisions that maximize the utility of the inhabitant from both the viewpoints of comfort and the cost paid for that comfort. Next, an experiment for verifying whether the presented model is effective or not, and its results are described. Finally, our model of the agent is discussed in relation to social intelligence design by investigating the interactive processes between the agent and the inhabitant. (shrink)

Most of the work in agent-based social simulation has assumed highly simplified agent models, with little attention being paid to the details of individual cognition. Here, in an effort to counteract that trend, we substitute a realistic cognitive agent model (CLARION) for the simpler models previously used in an organizational design task. On that basis, an exploration is made of the interaction between the cognitive parameters that govern individual agents, the placement of agents in different organizational structures, and the (...) performance of the organization. It is suggested that the two disciplines, cognitive modeling and social simulation, which have so far been pursued in relative isolation from each other, can be profitably integrated. (shrink)

Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view (Bowdle & Gentner, 2005), aptness view (Glucksberg & Haught, 2006b), and interpretive diversity view (Utsumi, 2007); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the choice between the categorization (...) and comparison processes. This article attempts to answer the question regarding which views are plausible by using cognitive modeling and computer simulation based on a semantic space model. In the simulation experiment, categorization and comparison processes are modeled in a semantic space constructed by latent semantic analysis. These two models receive word vectors for the constituent words of a metaphor and compute a vector for the metaphorical meaning. The resulting vectors can be evaluated according to the degree to which they mimic the human interpretation of the same metaphor; the maximum likelihood estimation determines which of the two models better explains the human interpretation. The result of the model selection is then predicted by three metaphor properties (i.e., vehicle conventionality, aptness, and interpretive diversity) to test the three views. The simulation experiment for Japanese metaphors demonstrates that both interpretive diversity and vehicle conventionality affect the choice between the two processes. On the other hand, it is found that metaphor aptness does not affect this choice. This result can be treated as computational evidence supporting the interpretive diversity and conventionality views. (shrink)

In this article, we develop a hierarchical Bayesian model of learning in a general type of artificial language-learning experiment in which learners are exposed to a mixture of grammars representing the variation present in real learners’ input, particularly at times of language change. The modeling goal is to formalize and quantify hypothesized learning biases. The test case is an experiment (Culbertson, Smolensky, & Legendre, 2012) targeting the learning of word-order patterns in the nominal domain. The model identifies (...) internal biases of the experimental participants, providing evidence that learners impose (possibly arbitrary) properties on the grammars they learn, potentially resulting in the cross-linguistic regularities known as typological universals. Learners exposed to mixtures of artificial grammars tended to shift those mixtures in certain ways rather than others; the model reveals how learners’ inferences are systematically affected by specific prior biases. These biases are in line with a typological generalization—Greenberg's Universal 18—which bans a particular word-order pattern relating nouns, adjectives, and numerals. (shrink)

Development of ontology development tools and ontology-enhanced software applications requires thorough understanding of ontology languages in order to implement them according to their specification. We present a formal specification of the ontologies part of the Web Services Modeling Language WSML documentation as a conceptual model in ORM2. Such an approach abstracts the semantics about ontological constructs, axioms, and properties from their implementation in arbitrary formats, thereby making the model easily understandable and reusable. This formal model in (...) ORM2, which is understandable by both logician and software developer, can be used as any other conceptual model to develop applications, thereby ensuring smooth transition from theory to implementations that are faithful to the theory. (shrink)

For Jari-Erik Nurmi, the practice of model-making in psychology is a complex process operating on different levels simultaneously. At first sight, his account seems to reflect Suppes' (1962) notion of a hierarchy of models: from low-level data models to high-level theoretical models, where at each level the model represents "structure" at a different degree of abstraction, and the levels are connected through structural isomorphism.1In this commentary, I want to complement and perhaps somewhat redirect Nurmi's analysis of his own (...) modeling efforts—away from the idea of an interconnected hierarchy of isomorphic structures, towards more autonomous roles of the models at different levels, each with its own .. (shrink)

We present a formal, mathematical model of argument structure and evaluation, taking seriously the procedural and dialogical aspects of argumentation. The model applies proof standards to determine the acceptability of statements on an issue-by-issue basis. The model uses different types of premises (ordinary premises, assumptions and exceptions) and information about the dialectical status of statements (stated, questioned, accepted or rejected) to allow the burden of proof to be allocated to the proponent or the respondent, as appropriate, for (...) each premise separately. Our approach allows the burden of proof for a premise to be assigned to a different party than the one who has the burden of proving the conclusion of the argument, and also to change the burden of proof or applicable proof standard as the dialogue progresses from stage to stage. Useful for modeling legal dialogues, the burden of production and burden of persuasion can be handled separately, with a different responsible party and applicable proof standard for each. Carneades enables critical questions of argumentation schemes to be modeled as additional premises, using premise types to capture the varying effect on the burden of proof of different kinds of questions. (shrink)

Does empirical work in economics both provoke and test theoretical models, or does model development proceed according to a theory-oriented research program, with little interaction with empirics? Robert Solow and Richard Lipsey have articulated different visions of this relationship. This paper: (i) describes these competing Solow versus Lipsey views; (ii) presents examples illustrating each view; and (iii) draws inferences about factors promoting a close relation between empirics and modeling. Three examples are examined in detail: the ?nursing shortage? literature; (...) Lind's analysis of recent rent control models; and a wide-ranging evaluation of ?is there too little theory in development economics?? by leading development economists. Various factors promoting or inhibiting a close connection between modeling and empirics are identified. (shrink)

The notion of a “familiar example” used in Page's definition of a “localist model” is shown to be meaningful only with respect to the types of tasks faced by the connectionist model. It is also shown that the modeling task ultimately dictates which choice of model: “localist” or “distributed” is most appropriate.

This paper argues that historical research is an important tool for modeling problem-solving in scientific invention and discovery. Two important cases in the history of modern physics—the invention of the transistor by John Bardeen and Walter Brattain and the development of the theory of superconductivity by Bardeen, Leon Cooper, and J. Robert Schrieffer—reveal factors essential to include in such a model. The focus is on problem-solving practices: problem decomposition, analogy, bridging principles, team-work, empirical tinkering, and library research. A (...) complete framework must encompass the full range of factors, including contingent individual traits and environmental circumstances. (shrink)

Van Gelder's example of a dynamical model is a Perceptron. The similarity of dynamical models and Perceptrons in turn exemplifies the close relationship between dynamical and algorithmic models. Both are models, not literal descriptions of brains. The brain states of standard modeling are better conceived as processes in the dynamical sense, but algorithmic models remain useful.

The differentiation of T Lymphocytes within the thymus is an important biological phenomenon during wich these cell acquire their functions to further control the immune system. Numerous experiments under various conditions have been devised to understand the different mechanisms involved in this complex process. Nevertheless, interpretation of these experiments lead to still contradictory debatable hypotheses. Modelisation of this process through classical simulation methods cannot be envisaged because they are not adapted to modifications of the model structure, which is the (...) point of interest. For these reasons, we proposed a new approach of automatic search for model. The program consists of four independent connected modules : The generator produces model, based on the rationale of formal grammars. Protocol and experimental data are stored in a set of experiments. The simulator using a protocol and a model provides simulated results. Finally, the supervisor by comparing simulated results and experimental data, adapts the model parameters to increase their fit and either chooses a new experiment to explore, or modifies the model structure. Change of the model structure is performed among still unexplored models according to their promise level, which is iteratively evaluated relatively to previously explored models through a proposed model distance. The generator is written in Prolog and the other modules in C++. The architecture of the program allows us to modify or complete a module without changing anything in the other modules. As a consequence, the proposed modeling approach conceived to study T lymphocyte differentiation within the thymus remains independent of this biological phenomenon and can be applied to other biological problems. (shrink)