Simulation in Science

There is an ongoing debate on whether or to what degree computer simulations can be likened to experiments. Many philosophers are sceptical whether a strict separation between the two categories is possible and deny that the materiality of experiments makes a difference (Morrison 2009, Parker 2009, Winsberg 2010). Some also like to describe computer simulations as a “third way” between experimental and theoretical research (Rohrlich 1990, Axelrod 2003, Kueppers/Lenhard 2005). In this article I defend the view that computer simulations are (...) not experiments but that they are tools for evaluating the consequences of theories and theoretical assumptions. In order to do so the (alleged) similarities and differences between simulations and experiments are examined. It is found that three fundamental differences between simulations and experiments remain: 1) Only experiments can generate new empirical data. 2) Only Experiments can operate directly on the target system. 3) Experiments alone can be employed for testing fundamental hypotheses. As a consequence, experiments enjoy a distinct epistemic role in science that cannot completely be superseded by computer simulations. This finding in connection with a discussion of border cases such as hybrid methods that combine measurement with simulation shows that computer simulations can clearly be distinguished from empirical methods. It is important to understand that computer simulations are not experiments, because otherwise there is a danger of systematically underestimating the need for empirical validation of simulations. (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)

Mission-oriented climate change research is often unverifiable. Therefore, many stakeholders look to peer-reviewed climate change research for trustworthy information about deeply uncertain and impactful phenomena. This is because peer-review signals that research has been vetted for scientific standards like reproducibility and replicability. Here we evaluate the transparency of research methodologies in mission-oriented computational climate research. We find that only five percent of our sample meets the minimal standard of fully open data and code required for reproducibility and replicability. The widespread (...) lack of minimal openness standards in peer-reviewed climate change research jeopardizes scientific credibility and risks poor societal outcomes as we manage growing climate risks. The scientific community can and must do better. We, the authors, outline necessary openness standards that we commit to as researchers, reviewers, and readers. We invite you to join us. (shrink)

Members of marginalized communities are often accused of being "too sensitive" when subjected to supposedly harmless acts of microaggression. This paper explores a simulated society consisting of marginalized and non-marginalized agents who interact and may, based on their individually held convictions, commit acts of microaggressions. Agents witnessing a microaggression might condone, ignore or condemn such microaggressions, thus potentially influencing a perpetrator's conviction. A prototype model has been implemented in NetLogo, and possible applications are briefly discussed.

In this paper, we pursue three general aims: (I) We will define a notion of fundamental opacity and ask whether it can be found in High Energy Physics (HEP), given the involvement of machine learning (ML) and computer simulations (CS) therein. (II) We identify two kinds of non-fundamental, contingent opacity associated with CS and ML in HEP respectively, and ask whether, and if so how, they may be overcome. (III) We address the question of whether any kind of opacity, contingent (...) or fundamental, is unique to ML or CS, or whether they stand in continuity to kinds of opacity associated with other scientific research. (shrink)

Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are not only data-laden, but data are also model-laden or model filtered. In this paper I elaborate and defend the second, more controversial, component of the symbiosis view. In particular, I construct a preliminary taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. These include data conversion, data correction, data interpolation, (...) data scaling, data fusion, data assimilation, and synthetic data. Each is defined and briefly illustrated with an example from the geosciences. I argue that model-filtered data are typically more accurate and reliable than the so-called raw data, and hence beneficially serve the epistemic aims of science. By illuminating the methods by which raw data are turned into scientifically useful data sets, this taxonomy provides a foundation for developing a more adequate philosophy of data. (shrink)

Neuralink could distribute artificial superintelligence to humans, thus allowing the homosapiens to synchronize the hemispheres of their brains, thereby transcending space-time, and potentially time traveling. While backwards time travel cannot change the past, due to paradoxes, the time traveler would probably share a soul with the alternate timeline self, thus providing closure for regrets, errors, injustice, etc. Plus, if one time travels with AI superintelligence, the time traveler may mend errors with greater ease. -/- Although other potential time travel methods (...) are displayed in the reference section, only the Gateway Process will be observed in this essay. The Gateway Process may allow for backwards time travel, under the rules that time travel cannot change the past, yet by attempting to change the past, new dimensions will be created, thus growing the universe. To determine if the Gateway Process allows for backwards time travel, researchers can use computer brain interface to examine the inside of a subject’s brain and mind. Plus, researchers can also check if the universe has grown after the subject has attempted to alter a past event, theoretically only creating another dimension. Soon technology may detect the exact expansion of the universe. Perhaps scientists can use space tunnels to investigate the possible creation of new dimensions from the Gateway Process backwards time traveling, attempting to alter past events. EXPERIMENT STEPS: 1)Automate the Gateway Process with Neuralink to ease suspected backwards time travel. 2)Connect the subject’s brain and mind to computer brain interface, or more specifically, magnetic resonance imaging, so the suspected time travel is recorded. 3)Build a space tunnel device to determine if the subject is creating new alternate dimensions with the suspected backwards time travel. 4)Stop, review and try again. Space tunnels may further corroborate if more dimensions have been created with the Gateway Process. Since hemisphere synchronization transcends the time-space dimension, effective enough Neuralink devices could allow someone to synchronize brain hemispheres and time travel to the past. Neuralink technology may both allow a deeper meditative state, thus backwards time travel, and computer monitoring of the backwards time travel and alternate dimension creation /universe expansion. At least presumably through scientific studies, each individual has alternate selves throughout alternate timelines thus, each individual(all alternate selves) become one in the afterlife. So backwards time traveling to correct a mistake, injustice, or error, thus creating alternate timelines, out of the past, would not change the original timeline but, would add a deeper satisfaction for the time traveler by sharing a soul with the alternative timeline self. While correcting the error, injustice, or mistake, the time traveler and alternative timeline self may share an individual consciousness. More concretely, quantum entanglement may illustrate how an individual’s selves, across different alternate timelines, share a deeper fundamental self, like a soul. I hereby invite experts in AI, quantum mechanics, and neuroscience to collaborate in adding technical rigor to this preprint. (shrink)

The concept of faster-than-light (FTL) motion challenges our fun- damental understanding of causality and relativity. This paper ex- plores a phenomenological model for velocity computation, examining the dependence of normalized velocity v/c on parameters such as the effective coupling Γx, the angle β, and terms incorporating lα and Θr. Multiple parameter configurations are investigated through numerical simulation to identify cases where velocities approach or exceed c, the speed of light. Key trends and observations are highlighted, providing a framework for future (...) theoretical work. (shrink)

This chapter examines modal modelling in climate science. It considers two related topics. The first is the use of climate models to attribute extreme weather events to climate change. The second is the interpretation and use of collections of climate models. Each topic is the subject of a current debate within climate science and philosophy of science, and each has an important modal component. The debates are similar in that each involves a contrast between probabilistic and non-probabilistic methods. In each (...) case, the chapter examines the kind of modal claims scientists make and how they are justified. As climate change is an important practical problem, each debate has a link to policy decisions, and so the chapter ends with a discussion of how modal modelling, and the possibilities it identifies, can support decision-making. (shrink)

How reliable are causal inferences in complex empirical scenarios? For example, a physician prescribes a drug to a patient, and then the patient undergoes various changes to their symptoms. They then increase their confidence that it is the drug that causes such changes. Are such inferences reliable guides to the causal relation in question, particularly when the physician can gain a large volume of such clinical experience by treating many patients? The evidence-based medicine movement says no, while some physicians and (...) philosophers support such appeals to first-person experience. We develop a formal model and simulate causal inference based on clinical experience. We conclude that in very particular clinical scenarios such inference can be reliable, while in many other routine clinical scenarios such inferences are not reliable. (shrink)

Computer simulations are nowadays often directly involved in the generation of experimental results. Given this dependency of experiments on computer simulations, that of simulations on models, and that of the models on free parameters, how do researchers establish trust in their experimental results? Using high-energy physics (HEP) as a case study, I will identify three different types of robustness that I call conceptual, methodological, and parametric robustness, and show how they can sanction this trust. However, as I will also show, (...) simulation models in HEP themselves fail to exhibit a type of robustness I call inverse parametric robustness. This combination of robustness and failures thereof is best understood by distinguishing different epistemic capacities of simulations and different senses of trust: Trusting simulations in their capacity to facilitate credible experimental results can mean accepting them as means for generating belief in these results, while this need not imply believing the models themselves in their capacity to represent an underlying reality. (shrink)

Scientific literacy is an essential aspect of an undergraduate education. Recipes for Science responds to this need by providing an accessible introduction to the nature of science and scientific methods appropriate for any beginning college student. The book is adaptable to a wide variety of different courses, such as introductions to scientific reasoning, methods courses in scientific disciplines, science education, and philosophy of science. -/- Recipes for Science ​​was first published in 2018, and a thoroughly revised second edition was published (...) in 2024. Special features include contemporary and historical case studies from many fields of physical, life, and social sciences; visual aids to clarify and illustrate ideas; text boxes to explore related topics; plenty of exercises to support student recall and application of concepts; suggestions for further readings at the end of each chapter; a glossary with helpful definitions of key terms; and a companion website with course syllabi, PowerPoint presentations, additional exercises, and original short videos on key topics. (shrink)

Research on concepts has concentrated on the way people apply concepts online, when presented with a stimulus. Just as important, however, is the use of concepts offline, when planning what to do or thinking about what is the case. There is strong evidence that inferences driven by conceptual thought draw heavily on special-purpose resources: sensory, motoric, affective, and evaluative. At the same time, concepts afford general-purpose recombination and support domain-general reasoning processes—phenomena that have long been the focus of philosophers. There (...) is a growing consensus that a theory of concepts must encompass both kinds of process. This book shows how concepts are able to act as an interface between general-purpose reasoning and special-purpose systems. Concept-driven thinking can take advantage of the complementary costs and benefits of each. The book lays out an empirically-based account of the different ways in which thinking with concepts takes us to new conclusions and underpins planning, decision-making, and action. It also spells out three useful implications of the account. First, it allows us to reconstruct the commonplace idea that thinking draws on the meaning of a concept. Second, it offers an insight into how human cognition avoids the frame problem and the complementary, less discussed, ‘if-then problem’ for nested processing dispositions. Third, it shows that metacognition can apply to concepts and concept-driven thinking in various ways. The framework developed in the book elucidates what it is that makes concept-driven thinking an especially powerful cognitive resource. (shrink)

This paper will discuss the recent LIGO-Virgo observations of gravitational waves and the binary black hole mergers that produce them. These observations rely on having prior knowledge of the dynamical behaviour of binary black hole systems, as governed by the Einstein Field Equations (EFEs). However, we currently lack any exact, analytic solutions to the EFEs describing such systems. In the absence of such solutions, a range of modelling approaches are used to mediate between the dynamical equations and the experimental data. (...) Models based on post-Newtonian approximation, the effective one-body formalism, and numerical relativity simulations (and combinations of these) bridge the gap between theory and observations and make the LIGO-Virgo experiments possible. In particular, this paper will consider how such models are validated as accurate descriptions of real-world binary black hole mergers (and the resulting gravitational waves) in the face of an epistemic circularity problem: the validity of these models must be assumed to justify claims about gravitational wave sources, but this validity can only be established based on these same observations. (shrink)

Observational astronomy is plagued with selection effects that must be taken into account when interpreting data from astronomical surveys. Because of the physical limitations of observing time and instrument sensitivity, datasets are rarely complete. However, determining specifically what is missing from any sample is not always straightforward. For example, there are always more faint objects (such as galaxies) than bright ones in any brightness-limited sample, but faint objects may not be of the same kind as bright ones. Assuming they are (...) can lead to mischaracterizing the population of objects near the boundary of what can be detected. Similarly, starting with nearby objects that can be well observed and assuming that objects much farther away (and sampled from a younger universe) are of the same kind can lead us astray. Demographic models of galaxy populations can be used as inputs to observing system simulations to create “mock” catalogues that can be used to characterize and account for multiple, interacting selection effects. The use of simulations for this purpose is common practice in astronomy, and blurs the line between observations and simulations; the observational data cannot be interpreted independent of the simulations. We will describe this methodology and argue that astrophysicists have developed effective ways to establish the reliability of simulation-dependent observational programs. The reliability depends on how well the physical and demographic properties of the simulated population can be constrained through independent observations. We also identify a new challenge raised by the use of simulations, which we call the “problem of uncomputed alternatives.” Sometimes the simulations themselves create unintended selection effects when the limits of what can be simulated lead astronomers to only consider a limited space of alternative proposals. (shrink)

Parameterization and parameter tuning are central aspects of climate modeling, and there is widespread consensus that these procedures involve certain subjective elements. Even if the use of these subjective elements is not necessarily epistemically problematic, there is an intuitive appeal for replacing them with more objective (automated) methods, such as machine learning. Relying on several case studies, we argue that, while machine learning techniques may help to improve climate model parameterization in several ways, they still require expert judgment that involves (...) subjective elements not so different from the ones arising in standard parameterization and tuning. The use of machine learning in parameterizations is an art as well as a science and requires careful supervision. (shrink)

This thesis investigates the possibility of a pluralistic approach in the field of Extreme Weather Event Attribution Studies between the Probability-Based Approach and the Storyline Approach through a thorough philosophical comparison of these methodologies based on their approach to defining events, their attribution measures, their reliance on historical data, their proneness to selection bias, and their value and error preferences when communicating results. As a result, the proposed scheme is a form of Integrative Pluralism based on the results of the (...) mentioned comparisons titled here as Non-Unificatory Local Integrative Pluralism which allows a non-unificationist integration between these methodologies on a local level while maintaining their boundaries along with their interaction on the other levels. -/- Supervised by: Prof. Dr. Mathias Frisch and Dr. Corey Dethier. (shrink)

I examine error diagnosis (model-model disagreement) in climate model intercomparisons including its difficulties, fruitful examples, and prospects for streamlining error diagnosis. I suggest that features of climate model intercomparisons pose a more significant challenge for error diagnosis than do features of individual model construction and complexity. Such features of intercomparisons include, e.g., the number of models involved, how models from different institutions interrelate, and what scientists know about each model. By considering numerous examples in the climate modeling literature, I distill (...) general strategies (e.g., employing physical reasoning and using dimension reduction techniques) used to diagnose model error. Based on these examples, I argue that an error repertoire could be beneficial for improving error diagnosis in climate modeling, although constructing one faces several difficulties. Finally, I suggest that the practice of error diagnosis demonstrates that scientists have a tacit-yet-working understanding of their models which has been under-appreciated by some philosophers. (shrink)

Explanation is commonly considered one of the central goals of science. Although computer simulations have become an important tool in many scientific areas, various philosophical concerns indicate that their explanatory power requires further scrutiny. We examine a case study in which atomistic simulations have been used to examine the factors responsible for the transport selectivity of certain channel proteins located at cell membranes. By elucidating how precisely atomistic simulations helped scientists draw inferences about the molecular system under investigation, we respond (...) to some concerns regarding their explanatory power. We argue that atomistic simulations can be tools for managing molecular complexity and for systematically assessing how the occurrence of the explanandum is sensitive to a range of factors. (shrink)

We simulate trial data to test speculative claims about research methods, such as the impact of publication bias.

Abstract : Associative work falls within the interests of the complementary social institutions to the official institutions in Moroccan society, as its intervention is based on voluntary work, and constitutes a mainstay by creating the appropriate conditions for framing and training, in order to build a responsible society that contributes to development and change, and working to integrate the individual into the process of social growth, Opening the field for creativity and highlighting the capabilities and skills for creation and innovation. (...) Keywords : Civil society, associative action, solidarity. ...........تقديم........ يدخل العمل الجمعوي ضمن المؤسسات الاجتماعية التكميلية للمؤسسات الرسمية بالمجتمع المغربي، ويشكل دعامة أساسية من خلال خلق الظروف المناسبة للتأطير والتكوين، من أجل بناء مجتمع مسؤول يساهم في التنمية والتغيير، والعمل على إدماج الفرد في عملية النمو الاجتماعي، وفتح المجال للإبداع وإبراز القدرات والمهارات على الخلق والابتكار. وفي ظل التحولات الكبيرة التي عرفها مغرب القرن الواحد والعشرين في مجموعة من المجالات الحيوية للبلاد، فرض خلالها العمل الجمعوي نفسه بشكل جلي خاصة على مستوى العمل التضامني في المناطق الواحية، في محاولة منه الاستجابة لحاجات الناس في ميادين ترتبط بالتعليم والصحة والفلاحة وإدماج المرأة والمتطلبات المعيشية.... وقد أولى المشرع المغربي عناية خاصة للعمل الجمعوي في الآونة الأخيرة، من خلال وضع إطار قانوني شامل يوضح القواعد المحددة لتأسيس الجمعيات، وكيفية سيرها ومختلف التحولات التي قد تصادفها خلال حياتها، خاصة مع دستور2011 الذي عزز من قيمة وفعالية العمل الجمعوي بكونه أحد المكونات الأساسية للمجتمع المدني المغربي، باعتباره آلية من آليات تنزيل مقتضيات الديمقراطية التشاركية. ويعد التضامن الاجتماعي من المرتكزات الأساسية التي يقوم عليها المجتمع الواحي بالمغرب، وخاصة القروي منه، باعتباره مجتمعا قبليا في الأصل، حيث يساعد الأفراد بعضهم بعضا لمواجهة مصاعب الحياة، فيكونون أسرة واحدة، يعين غنيهم فقيرهم، ويساعد قويهم ضعيفهم، ويشترك الجميع في الأفراح والأتراح. ومن هذا المنطلق يحق لنا التساؤل حول حقيقة العمل الجمعوي بواحات زيز الأوسط تافيلالت؟ وما هي مجالات إسهاماته؟ وأين تتجلى هذه الإسهامات؟ وهل فعلا ينجز عملا تضامنيا لتحقيق المساعدة والتكافل والتآزر؟ وهل يدرك الفاعلون الاجتماعيون حقيقة هذا الدور داخل واحات زيز الأوسط؟ أم هو عبارة عن آلية لإنتاج وإعادة إنتاج المألوف؟ للإجابة عن هذه الأسئلة وغيرها، تم النزول للميدان وجمع المعطيات الضرورية وتفريغها وتحليلها حسب النموذج الإحصائي. بناء على إشكالية وفرضيات بمتغيرات دقيقة، واعتماد الاستمارة كأداة لجمع البيانات، غير أنه لا يمكن أن نتطرق إلى جميع محطات هذا البحث الميداني نظرا لضيق المجال، لذلك سأحاول إثارة بعض المراحل المنهجية الكبرى والنتائج والتوصيات. (shrink)

Computer simulations have conventionally been understood to be either extensions of formal methods such as mathematical models or as special cases of empirical practices such as experiments. Here, I argue that computer simulations are best understood as instruments. Understanding them as such can better elucidate their actual role as well as their potential epistemic standing in relation to science and other scientific methods, practices and devices.

This paper considers hybrid systems — dynamical systems that exhibit both continuous and discrete behavior. Usually, in these systems, interactions between the continuous and discrete dynamics occur when a pre-defined function becomes equal to zero, i.e., in the system occurs a zero-crossing (the situation where the function only “touches” zero is considered as the zero-crossing, as well). Determination of zero-crossings plays a crucial role in the correct simulation of the system in this case. However, for models of many real-life hybrid (...) systems, such interactions may lead to the so-called Zeno executions, i.e., situations where the system undergoes an unbounded number of discrete transitions in a finite and bounded length of time. In this case, standard numerical methods of simulating the systems may fail, since the time between two transitions can decrease significantly leading to ill-conditioning of the simulation. Correct determination of zero-crossings for a complex real-life system can require a lot of computational resources and, as a consequence, slow down the simulation significantly. This paper presents a new way to execute the simulation generating time observations of the hybrid system dynamically using numerical infinitesimals introduced recently, allowing thus to determine zero-crossings more accurately. The proposed method allows to automatically detect zero-crossings with predefined accuracy and to analyze better the behavior of the system around the zero-crossings generating observations more densely, where it is necessary. Moreover, the search for zero-crossings is performed efficiently without re-evaluation of the whole system at each observation. To show the validity of the proposed algorithm, the well-known Bouncing Ball hybrid system has been studied and the obtained simulation results were compared with the standard method. (shrink)

Previous simulation models have found positive effects of cognitive diversity on group performance, but have not explored effects of diversity in demographics (e.g., gender, ethnicity). In this paper, we present an agent-based model that captures two empirically supported hypotheses about how demographic diversity can improve group performance. The results of our simulations suggest that, even when social identities are not associated with distinctive task-related cognitive resources, demographic diversity can, in certain circumstances, benefit collective performance by counteracting two types of conformity (...) that can arise in homogeneous groups: those relating to group-based trust and those connected to normative expectations towards in-groups. (shrink)

Objectives To explore how factors relating to grades and grading affect the correctness of choices that grant-review panels make among submitted proposals. To identify interventions in panel design that may be expected to increase the correctness of choices. -/- Method Experimentation with an empirically-calibrated computer simulation model of panel review. Model parameters are set in accordance with procedures at a national science funding agency. Correctness of choices among research proposals is operationalized as agreement with the choices of an elite panel. (...) -/- Conclusions The simulation model generates several hypotheses to guide further research. Increasing the number of grades used by panel members increases the correctness of simulated choices among submitted proposals. Collective decision procedures giving panels a greater capacity for discriminating among proposals also increase correctness. Surprisingly, differences in grading standards among panel members do not appreciably decrease correctness. (shrink)

This essay replies to Michael Morreau and Erik J. Olsson’s ‘Learning from Ranters: The Effect of Information Resistance on the Epistemic Quality of Social Network Deliberation’. Morreau and Olsson use simulations to suggest that false ranters—agents who do not update their beliefs and only ever assert false claims—do not diminish the epistemic value of deliberation for other agents and can even be epistemically valuable. They argue conclude that “Our study suggests that including [false] ranters has little or no negative effect (...) on the epistemic value of social deliberation. Including them can even be epistemically beneficial. -/- I present concerns about their model and I enumerate some epistemic values that their discussion omits. I first raise two interrelated worries: (i.) The model is too simple; real-life irresponsible assertors do not speak uniformly falsely, for example. And tracking testifiers’ reliability demands cognitive resources. (ii.) In reality, we do not treat a person’s assertions that p as evidence that not p, especially not for all their assertions. I argue that these simplifications threat Morreau and Olsson conclusion. -/- I then enumerate epistemic values and disvalues that Morreau and Olsson do not discuss, but which bear on the value of false assertions and false ranters in their simulation and in real life. Candidate disvalues include: False beliefs of ranters; cognitive costs of discerning and recalling testifiers’ reliability; distrust; epistemic polarisatin; a prevalence of false assertion can impugn all testimony, including that of reliable testifiers. And candidate values include: a prevalence of true beliefs and assertions; attention being directed towards the right things; well-functioning trust relationships; believing people’s assertions; healthy discussion; epistemic respect; learning together. -/- . (shrink)

This book presents fresh insights into analogue quantum simulation. It argues that these simulations are a new instrument of science. They require a bespoke philosophical analysis, sensitive to both the similarities to and the differences with conventional scientific practices such as analogical argument, experimentation, and classical simulation. -/- The analysis situates the various forms of analogue quantum simulation on the methodological map of modern science. In doing so, it clarifies the functions that analogue quantum simulation serves in scientific practice. To (...) this end, the authors introduce a number of important terminological distinctions. They establish that analogue quantum ‘computation' and ‘emulation' are distinct scientific practices and lead to distinct forms of scientific understanding. The authors also demonstrate the normative value of the computation vs. emulation distinction at both an epistemic and a pragmatic level. -/- The volume features a range of detailed case studies focusing on: i) cold atom computation of many-body localisation and the Higgs mode; ii) photonic emulation of quantum effects in biological systems; and iii) emulation of Hawking radiation in dispersive optical media. Overall, readers will discover a normative framework to isolate and support the goals of scientists undertaking analogue quantum simulation and emulation. This framework will prove useful to both working scientists and philosophers of science interested in cutting-edge scientific practice. (shrink)

Starting in the 1950s, computer programs for simulating cognitive processes and intelligent behaviour were the hallmark of Good Old-Fashioned Artificial Intelligence and ‘cognitivist’ cognitive science. This article examines a somewhat neglected case of simulation pursued by one of the founding fathers of simulation methodology, Herbert A. Simon. In the 1970s and 1980s, Simon had repeated contacts with Marxist countries and scientists, in the context of which he advanced the idea that cognitivism could be used as a framework for simulating dialectical (...) materialism. Simon's idea was, in particular, to represent dialectical processes through a ‘symbolic’ version of dialectical logic. This article explores the context of Simon's interaction with Marxist countries—China and the USSR—and also assesses the outcome of the simulation. The difficulty with simulating distinctive features of dialectical materialism is read in light of the underlying assumptions of cognitivism and, ultimately, in light of the attempt to tame a rival world view. (shrink)

On entend généralement par « théorie des modèles » autant la métamathématique (ou sémantique formelle) que la sémantique des modèles des sciences non formelles. Cet article a pour objet la théorie des modèles scientifiques que Mario Bunge a développée dans Method, Models and Matter (1973). J’y analyse l’intégration théorique qu’opère Bunge des sciences formelles et des sciences expérimentales ou observationnelles, laquelle prend appui sur sa philosophie des sciences. Je la compare sommairement à la théorie des modèles de Gilles-Gaston Granger dans (...) le but évident d’en dégager les ressemblances et les dissimilitudes, mais aussi leur commun point d’achoppement : l’une comme l’autre usent en effet d’un concept non analysé dont la fonction épistémologique est pourtant capitale et produit les mêmes effets. Au centre de la théorie des modèles de Bunge se trouve le concept de simulation que je comparerai à celui qui est en usage dans les sciences de l’ordinateur et qui est de nos jours largement appliqué à diverses sciences, tant sociales que naturelles. Je conclurai sur les conséquences méthodologiques et métaphysiques de la théorie bungéenne des modèles. (shrink)

In this paper, we argue that computer simulations can provide valuable insights into the performance of voting methods on different collective decision problems. This could improve institutional design, even when there is no general theoretical result to support the optimality of a voting method. To support our claim, we first describe a decision problem that has not received much theoretical attention in the literature. We outline different voting methods to address that collective decision problem. Under certain criteria of assessment akin (...) to extensions of the Condorcet Jury Theorem, we run simulations for the methods using MATLAB, in order to compare their performance under various conditions. We consider and respond to concerns about the use of simulations in the assessment of voting procedures for policymaking. (shrink)

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection ft into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the feld. Moreover, we (...) argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond. (shrink)

How could the initial, drastic decisions to implement “lockdowns” to control the spread of COVID-19 infections be justifiable, when they were made on the basis of such uncertain evidence? We defend the imposition of lockdowns in some countries by first, and focusing on the UK, looking at the evidence that undergirded the decision, second, arguing that this provided us with sufficient grounds to restrict liberty given the circumstances, and third, defending the use of poorly-empirically-constrained epidemiological models as tools that can (...) legitimately guide public policy. (shrink)

In philosophical studies regarding mathematical models of dynamical systems, instability due to sensitive dependence on initial conditions, on the one side, and instability due to sensitive dependence on model structure, on the other, have by now been extensively discussed. Yet there is a third kind of instability, which by contrast has thus far been rather overlooked, that is also a challenge for model predictions about dynamical systems. This is the numerical instability due to the employment of numerical methods involving a (...) discretization process, where discretization is required to solve the differential equations of dynamical systems on a computer. We argue that the criteria for numerical stability, as usually provided by numerical analysis textbooks, are insufficient, and, after mentioning the promising development of backward analysis, we discuss to what extent, in practice, numerical instability can be controlled or avoided. (shrink)

We argue that the appraisal of models in social epistemology requires conceiving of them as argumentative devices, taking into account the argumentative context and adopting a family-of-models perspective. We draw up such an account and show how it makes it easier to see the value and limits of the use of models in social epistemology. To illustrate our points, we document and explicate the argumentative role of epistemic landscape models in social epistemology and highlight their limitations. We also claim that (...) our account could be fruitfully used in appraising other models in philosophy and science. (shrink)

Computer simulations are often claimed to be opaque and thus to lack transparency. But what exactly is the opacity of simulations? This paper aims to answer that question by proposing an explication of opacity. Such an explication is needed, I argue, because the pioneering definition of opacity by P. Humphreys and a recent elaboration by Durán and Formanek are too narrow. While it is true that simulations are opaque in that they include too many computations and thus cannot be checked (...) by hand, this doesn’t exhaust what we might want to call the opacity of simulations. I thus make a fresh start with the natural idea that the opacity of a method is its disposition to resist knowledge and understanding. I draw on recent work on understanding and elaborate the idea by a systematic investigation into what type of knowledge and what type of understanding are required if opacity is to be avoided and why the required sort of understanding, in particular, is difficult to achieve. My proposal is that a method is opaque to the degree that it’s difficult for humans to know and to understand why its outcomes arise. This proposal allows for a comparison between different methods regarding opacity. It further refers to a kind of epistemic access that is important in scientific work with simulations. (shrink)

With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 26 May 2021 to ©The Author(s) 2021 and the article is forthwith distributed under a Creative Commons Attribution.

Researchers often pursue proof of concept research, but criteria for evaluating such research remain poorly specified. This article proposes a general framework for proof of concept research that k...

This paper is dedicated to numerical computation of higher order derivatives in Simulink. In this paper, a new module has been implemented to achieve this purpose within the Simulink-based Infinity Computer solution, recently introduced by the authors. This module offers several blocks to calculate higher order derivatives of a function given by the arithmetic operations and elementary functions. Traditionally, this can be done in Simulink using finite differences only, for which it is well-known that they can be characterized by instability (...) and low accuracy. Moreover, the proposed module allows to calculate higher order Lie derivatives embedded in the numerical solution to Ordinary Differential Equations (ODEs). Traditionally, Simulink does not offer any practical solution for this case without using difficult external libraries and methodologies, which are domain-specific, not general-purpose and have their own limitations. The proposed differentiation module bridges this gap, is simple and does not require any additional knowledge or skills except basic knowledge of the Simulink programming language. Finally, the block for constructing the Taylor expansion of the differentiated function is also proposed, adding so another efficient numerical method for solving ODEs and for polynomial approximation of the functions. Numerical experiments on several classes of test problems confirm advantages of the proposed solution. (shrink)

Causal Bayes nets (CBNs) can be used to model causal relationships up to whole mechanisms. Though modelling mechanisms with CBNs comes with many advantages, CBNs might fail to adequately represent some biological mechanisms because—as Kaiser (2016) pointed out—they have problems with capturing relevant spatial and structural information. In this paper we propose a hybrid approach for modelling mechanisms that combines CBNs and cellular automata. Our approach can incorporate spatial and structural information while, at the same time, it comes with all (...) the merits of a CBN representation of mechanisms. (shrink)

The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across the (...) traditional dichotomies between symbolic and embodied AI, general intelligence and symbol and intelligence and cognitive simulation and human/non-human-like AI. -/- According to the taxonomy proposed here, one can distinguish between four distinct general approaches that figured prominently in early and classical AI, and that have partly developed into distinct research programs: first, phenomenal simulations (e.g., Turing’s “imitation game”); second, simulations that explore general-level formal isomorphisms in pursuit of a general theory of intelligence (e.g., logic-based AI); third, simulations as exploratory material models that serve to develop theoretical accounts of cognitive processes (e.g., Marr’s stages of visual processing and classical connectionism); and fourth, simulations as strictly formal models of a theory of computation that postulates cognitive processes to be isomorphic with computational processes (strong symbolic AI). -/- In continuation of pragmatic views of the modes of modeling and simulating world affairs, this taxonomy of approaches to modeling in AI helps to elucidate how available computational concepts and simulational resources contribute to the modes of representation and theory development in AI research—and what made that research program uniquely dependent on them. (shrink)

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that demand less computer processor time. Such models are generally simpler in the sense of being more idealized, or less realistic. So modelers face a trade-off between realism and uncertainty quantification. Seeing this trade-off for the important epistemic issue (...) that it is requires a shift in perspective from the established simplicity literature in philosophy of science. (shrink)

Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked in accounts (...) of reproducibility issues. Software is not only about designing and coding but also about maintaining, supporting, distributing, licensing, and governance; it is not only about developers but also about users. We focus on openness debates among computational chemists involved in molecular modeling software packages as empirical grounding for our argument. We then identify and analyse four epistemic characteristics as key to the role of software in computational reproducibility. (shrink)

Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.

A Série Investigação Filosófica, uma iniciativa do Núcleo de Ensino e Pesquisa em Filosofia do Departamento de Filosofia da UFPel e do Grupo de Pesquisa Investigação Filosófica do Departamento de Filosofia da UNIFAP, sob o selo editorial do NEPFil online e da Editora da Universidade Federal de Pelotas, com auxílio financeiro da John Templeton Foundation, tem por objetivo precípuo a publicação da tradução para a língua portuguesa de textos selecionados a partir de diversas plataformas internacionalmente reconhecidas, tal como a Stanford (...) Encyclopedia of Philosophy, por exemplo. O objetivo geral da série é disponibilizar materiais bibliográficos relevantes tanto para a utilização enquanto material didático quanto para a própria investigação filosófica. (shrink)

Climatologists have recently introduced a distinction between projections as scenario-based model results on the one hand and predictions on the other hand. The interpretation and usage of both terms is, however, not univocal. It is stated that the ambiguities of the interpretations may cause problems in the communication of climate science within the scientific community and to the public realm. This paper suggests an account of scenarios as props in games of make-belive. With this account, we explain the difference between (...) projections that should be make-believed and other model results that should be believed. (shrink)

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits (...) of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum. (shrink)

We were slightly concerned, upon having read Eric Winsberg, Jason Brennan and Chris Surprenant’s reply to our paper “Were Lockdowns Justified? A Return to the Facts and Evidence”, that they may have fundamentally misunderstood the nature of our argument, so we issue the following clarification, along with a comment on our motivations for writing such a piece, for the interested reader.