We explore three questions about Earth system modeling that are of both scientific and philosophical interest: What kind of understanding can be gained via complex Earth system models? How can the limits of understanding be bypassed or managed? How should the task of evaluating Earth system models be conceptualized?

Efforts to bridge emotion theory with neurobiology can be facilitated by dynamic systems (DS) modeling. DS principles stipulate higher-order wholes emerging from lower-order constituents through bidirectional causal processes cognition relations. I then present a psychological model based on this reconceptualization, identifying trigger, self-amplification, and self-stabilization phases of emotion-appraisal states, leading to consolidating traits. The article goes on to describe neural structures and functions involved in appraisal and emotion, as well as DS mechanisms of integration by which they interact. (...) These mechanisms include nested feedback interactions, global effects of neuromodulation, vertical integration, action-monitoring, and synaptic plasticity, and they are modeled in terms of both functional integration and temporal synchronization. I end by elaborating the psychological model of emotion–appraisal states with reference to neural processes. (shrink)

Lewis neglects cross-cultural data in his dynamic systems model of emotion, probably because appraisal theory disregards behavior and because anthropologists have not engaged discussions of neural plasticity in the brain sciences. Considering cultural variation in emotion-related behavior, such as grieving, indigenous descriptions of emotions, and alternative developmental regimens, such as sport, opens up avenues to test dynamic systems models.

Lewis proposes a “reconceptualization” of how to link the psychology and neurobiology of emotion and cognitive-emotional interactions. His main proposed themes have actually been actively and quantitatively developed in the neural modeling literature for more than 30 years. This commentary summarizes some of these themes and points to areas of particularly active research in this area.

Bridging between psychological and neurobiological systems requires that the system components are closely specified at both the psychological and brain levels of analysis. We argue that in developing his dynamic systems theory framework, Lewis has sidestepped the notion of a psychological level systems model altogether, and has taken a partisan approach to his exposition of a brain-level systems model.

It is largely acknowledged that natural languages emerge not just from human brains but also from rich communities of interacting human brains (Senghas, ). Yet the precise role of such communities and such interaction in the emergence of core properties of language has largely gone uninvestigated in naturally emerging systems, leaving the few existing computational investigations of this issue at an artificial setting. Here, we take a step toward investigating the precise role of community structure in the emergence of (...) linguistic conventions with both naturalistic empirical data and computational modeling. We first show conventionalization of lexicons in two different classes of naturally emerging signed systems: (a) protolinguistic “homesigns” invented by linguistically isolated Deaf individuals, and (b) a natural sign language emerging in a recently formed rich Deaf community. We find that the latter conventionalized faster than the former. Second, we model conventionalization as a population of interacting individuals who adjust their probability of sign use in response to other individuals' actual sign use, following an independently motivated model of language learning (Yang, , ). Simulations suggest that a richer social network, like that of natural (signed) languages, conventionalizes faster than a sparser social network, like that of homesign systems. We discuss our behavioral and computational results in light of other work on language emergence, and other work of behavior on complex networks. (shrink)

Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a (...) class='Hi'>modeling approach, Agent-based Computational Economics, that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented and explained. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing. (shrink)

Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational (...) simulation and other tools to handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations. (shrink)

This essay provides an introduction to the terminology, concepts, methods, and challenges of image‐based modeling in biology. Image‐based modeling and simulation aims at using systematic, quantitative image data to build predictive models of biological systems that can be simulated with a computer. This allows one to disentangle molecular mechanisms from effects of shape and geometry. Questions like “what is the functional role of shape” or “how are biological shapes generated and regulated” can be addressed in the framework (...) of image‐based systems biology. The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum. (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)

The paper presents the most general aspects of scientific modeling and shows that social systems naturally include different belief systems. Belief systems differ in a variety of respects, most notably in the selection of suitable qualities to encode and the internal structure of the observables. The following results emerge from the analysis: conflict is explained by showing that different models encode different qualities, which implies that they model different realities; explicitly connecting models to the realities that (...) they encode makes it possible to clarify the relations among models; by understanding that social systems are complex one knows that there is no chance of developing a maximal model of the system; the distinction among different levels of depth implicitly includes a strategy for inducing change; identity-preserving models are among the most difficult to modify; since models do not customarily generate internal signals of error, strategies with which to determine when models are out of synch with their situations are especially valuable; changing the form of power from a zero sum game to a positive sum game helps transform the nature of conflicts. (shrink)

Ecologist Richard Levins argues population biologists must trade-off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade-off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail (...) since Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

At present, high-tech enterprises are mainly organizations engaged in the production, research, and development and service of high-tech products. The current development of high-tech industries in various countries in the world is of great significance to improving social productivity and overall national strength. This article mainly introduces the modeling and analysis of the complex system of human capital accumulation in high-tech enterprises based on big data. This paper proposes a theoretical analysis of corporate human capital data and proposes regression (...) analysis and analytic hierarchy process to calculate and analyze the process of corporate human capital accumulation and collect and analyze the data using questionnaire surveys and other methods. In addition, complex systems were modeled based on big data, and a cloud computing-based human capital big data analysis platform was established. The experimental results show that complex system modeling based on big data has a positive impact on the human capital accumulation of high-tech enterprises. For high-tech companies at different stages of development, the relationship between various types of human capital and corporate performance is inconsistent with the market economy. In contrast, the current salary system of some high-tech companies still has many drawbacks. The cost of using human resources controlled by the wage system accounts for more than 24%. (shrink)

This paper explores some issues concerning how we should think about interventions (in the sense of unconfounded manipulations) of "upper-level" variables in contexts in which these supervene on but are not identical with lower-level realizers. It is argued that we should reject the demand that interventions on upper-level variables must leave their lower-level realizers unchanged– a requirement that within an interventionist framework would imply that upper-level variables are causally inert. Instead an intervention on an upper-level variable at the same time (...) changes its lower-level realizer in a way that is consistent with the change in the upper- level variable. The lower-level realizer should not be regarded as a potential "confounder" of upper-level causal relations, as in "exclusionist" arguments. Several proposals for making this precise are considered and several pro-exclusionist arguments are criticized. (shrink)

The purpose of the study is to establish a causal relationship of job satisfaction depending on the average number of employees, the level of wages, the number of applications and the time factor. The article deals with the problem of modeling socio-economic satisfaction with the work of employees in the provision of public services. Based on the correlation analysis, linear and nonlinear models of the interrelationships of factors related to this problem are formed. Econometric models have been developed to (...) effectively assess the level of satisfaction of employees in the provision of public services. The scientific novelty lies in the study of new models that are statistically superior to domestic developments in this field of activity. As a result, the most significant factors affecting the level of job satisfaction were identified. (shrink)

Recent work by Frigg et. al. and Mayo-Wilson have called attention to a particular sort of error associated with attempts to model certain complex systems: structural modeling error. The assessment of the degree of SME in a model presupposes agreement between modelers about the best way to individuate natural systems, an agreement which can be more problematic than it appears. This problem, which we dub “the system individuation problem” arises in many of the same contexts as SME, (...) and the two often compound one another. This paper explores the common roots of the two problems in concerns about the precision of predictions generated by scientific models, and discusses how both concerns bear on the study of complex natural systems, particularly the global climate. (shrink)

In international relations theory, there is a long history of Richardson-like modeling of the evolution of military capability. Usually, such models are deterministic and predictive and do not allow for the representation of the transition from competitive peace to shooting war. More recently, models have been developed which attempt to represent the evolution of relationship between nations. The relationship between nations, varying from friendship to hostility, is taken to be synonymous with the intent of nations towards each other, varying (...) from good will to malice. Generally, these relationship models do not include capability though common sense would indicate that capability and mutual intent should profoundly influence each other. A model is presented here which combines these two fundamental attributes of international relations and attempts to represent the outbreak of war in the world system by the onset of deterministic chaos in the extended model. (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.

We develop a general covariant categorical modeling theory of natural systems’ behavior based on the fundamental functorial processes of representation and localization-globalization. In the first part of this study we analyze the process of representation. Representation constitutes a categorical modeling relation that signifies the semantic bidirectional process of correspondence between natural systems and formal symbolic systems. The notion of formal systems is substantiated by algebraic rings of observable attributes of natural systems. In this (...) perspective, the distinction between simple and complex systems is reflected in the appropriate qualification of their corresponding rings of observables. The crucial distinguishing requirement with respect to the coordinatizing rings of observables has to do with the property of global commutativity. The global information structure representing the behavior of a complex system is modeled functorially in terms of its Spectrum functor. Due to the fact that, the fundamental process of representation is bidirectional by construction, it admits a precise categorical formulation in terms of the syntactic language of adjoint functors, constituting thus, a categorical adjunction. The left adjoint functor of this adjunction signifies the process of encoding the information related with phenomena of natural systems in terms of coordinatizing rings of observables, whereas, the right adjoint functor signifies the inverse process of information decoding, which, can be used for making predictions about the behavior of natural systems. (shrink)

We develop a general covariant categorical modeling theory of natural systems' behavior based on the fundamental functorial processes of representation and localization-globalization. In the second part of this study we analyze the semantic bidirectional process of localization-globalization. The notion of a localization system of a complex information structure bears a dual role: Firstly, it determines the appropriate categorical environment of base reference contexts for considering the operational modeling of a complex system's behavior, and secondly, it specifies the (...) global compatibility conditions of local contextual information. A localization system acts on the global information structure of a complex system, partitions it into sorts, and eventually, forces the consistent sheaf-theoretic fibering of the latter over the base category of commutative reference contexts. In this manner, the sheafification of the Spectrum functor of a complex information structure takes place by imposing on the uniform and homologous fibered structure of elements of the Spectrum presheaf the following two requirements of coherence in relation to the localization-globalization process: [i]. Compatibility of information under restriction from the global to the local level, and [ii]. Compatibility of information under extension from the local to the global level. Correspondingly, the options of local and global receive a concrete mathematical meaning with respect to a suitable notion of topology (categorical Grothendieck topology) defined on the base category of commutative reference contexts. Finally, the accurate functorial process modeling of a complex system's behavior, respecting the processes of representation and localization-globalization, is being effectuated by means of establishing a categorical dual equivalence between the category of complex information structures, and the topes of sheaves over the base category of partial or local information carriers, equipped with the categorical topology of epimorphosis families. (shrink)

One of the major issues for user assistance systems consists of “providing help at an appropriate level”. In this paper we analyze the problem of modeling task experience — a prerequisite for provisioning adequate help. In contrast to level-based approaches we propose an ontology-based model, which allows fine-grained modeling of task experience using the concepts of the task domain as granules. The model is semantic in the sense that it allows to take advantage of the relations between (...) concepts to provide novel semantic services and interactions. We present the SACHS (Semantic Annotations for a Controlling Help System, a semantic help system for a spreadsheet-based financial controlling system) software as an exemplary application of the proposed task experience model. (shrink)

This paper aims to reconfigure the place of memory in epistemology. I start by rethinking the problem that memory systems solve; rather than merely functioning to store information, I argue that the core function of any memory system is to support accurate and relevant retrieval. This way of specifying the function of memory has consequences for which structures and mechanisms make up a memory system. In brief, memory systems are modeling systems. This means that they generate, (...) update and manage a series of overlapping, simplified, relational representations that map out features of the world. Succeeding at building and maintaining models requires the kind of active knowledge generation traditionally associated only with deliberative reasoning. (shrink)

This article introduces an agent-based and a system-dynamics model investigating the cultural transmission of frequent collective rituals. It focuses on social function and cognitive attraction as independently affecting transmission. The models focus on the historical context of early Christian meals, where various theoretically inspiring trends in cultural transmission of rituals can be observed. The primary purpose of the article is to contribute to theorizing about cultural transmission of rituals by suggesting a clear operationalization of their social function and cognitive attraction. (...) Furthermore, the article challenges recent trends in the field by providing a theoretically feasible model for how, under certain conditions, cognitive attraction can influence the transmission to a relatively greater extent than social function. In the system dynamics model we reproduce the results of our agent-based model while putting some of our basic operational assumptions under scrutiny. We consider approaching social function and cognitive attraction in isolation as a preliminary but necessary step in the process of creating more complex models of the cultural selection of rituals, where the two aspects will be combined to produce ritual forms with greater correspondence to real-world religious rituals. (shrink)

The influence of many factors on ecological success in common pool resource management is still unclear. This may be due to methodological issues. These include causal complexity, a lack of large-N-studies and nonlinear relationships between factors. We address all three issues with a new methodological approach, artificial neural networks, which is discussed in detail. It allows us to develop a model with comparably high predictive power. In addition, two success factors are analyzed: legal security and institutional fairness. Both factors show (...) a positive impact on success in irrigation and fisheries supporting the view that there are sector-independent success factors. (shrink)

In order to solve a system of nonlinear rate equations one can try to use some soliton methods. The procedure involves three steps: find a ‘Lax representation’ where all the kinetic variables are combined into a single matrix \, all the kinetic constants are encoded in a matrix H; find a Darboux–Bäcklund dressing transformation for the Lax representation \]\), where f models a time-dependent environment; find a class of seed solutions \ that lead, via a nontrivial chain of dressings \ (...) to new solutions, difficult to find by other methods. The latter step is not a trivial one since a non-soliton method has to be employed to find an appropriate initial \. Procedures that lead to a correct \ have been discussed in the literature only for a limited class of H and f. Here, we develop a formalism that works for practically any H, and any explicitly time-dependent f. As a result, we are able to find exact solutions to a system of equations describing an arbitrary number of species interacting through catalytic feedbacks, with general time dependent parameters characterizing the nonlinearity. Explicit examples involve up to 42 interacting species. (shrink)

This article explores the development of a rat model of mother-infant relationships from its origins in the psychosomatic investigations of the mid-1960s to its elaboration into a theoretical system in neurobiology. I reconstruct the research trajectory of a group of neurobiologists in the United States, with a focus on the experimental practices they adopted while building this animal model. Providing a microhistory of this decade-long undertaking, I show that what drove the development of the model in practice was a serendipitous (...) finding about infants’ response to maternal separation. Detected inadvertently, the pup’s separation response acquired an epistemic significance of its own and reoriented the experimental system towards unanticipated paths. To explain this intriguing phenomenon, the neurobiologists kept on refining their material manipulations and stabilizing their experimental outcomes. They thus established a series of causal relationships that connected dysregulations of the infant’s physiological systems to disruptions in maternal care. As important as this interactive stabilization of technique and objects in the laboratory was how the researchers theorized the network of relationships derived from this technically constituted objectivity. Highlighting the practice-driven aspects of model-building, I demonstrate that what facilitated this theoretical process was an integrated design of complementary experiments. The outcome of each separate experiment of the research program came to bear upon the outcomes of other experiments, informing the development of future manipulations. It was this strategically driven integration process that allowed the experimenters to build expanding networks of causal relationships and consolidate them into a neurobiological theory. (shrink)

The study considers the development of methods for detecting anomalous network connections based on hybridization of computational intelligence methods. An analysis of approaches to detecting anomalies and abuses in computer networks. In the framework of this analysis, a classification of methods for detecting network attacks is proposed. The main results are reduced to the construction of multi-class models that increase the efficiency of the attack detection system, and can be used to build systems for classifying network parameters during the (...) attack. A model of an artificial immune system based on an evolutionary approach, an algorithm for genetic-competitive learning of the Kohonen network and a method of hierarchical hybridization of binary classifiers with the addition to the detection of anomalous network connections have been developed. The architecture of the network distributed attack detection system has been developed. The architecture of the attack detection system is two-tier: the first level provides the primary analysis of individual packets and network connections using signature analysis, the second level processes the processing of aggregate network data streams using adaptive classifiers. A signature analysis was performed to study network performance based on the Aho-Korasik and Boyer-Moore algorithms and their improved analogues were implemented using OpenMP and CUDA technologies. The architecture is presented and the main points of operation of the network attack generator are shown. A system for generating network attacks has been developed. This system consists of two components: an asynchronous transparent proxy server for TCP sessions and a frontend interface for a network attack generator. The results of the experiments confirmed that the functional and non-functional requirements, as well as the requirements for computing intelligent systems, are met for the developed attack detection system. (shrink)

A double delayed hybrid stochastic prey-predator bioeconomic system with Lévy jumps is established and analyzed, where commercial harvesting on prey and environmental stochasticity on population dynamics are considered. Two discrete time delays are utilized to represent the maturation delay of prey and gestation delay of predator, respectively. For a deterministic system, positivity of solutions and uniform persistence of system are discussed. Some sufficient conditions associated with double time delays are derived to discuss asymptotic stability of interior equilibrium. For a stochastic (...) system, existence and uniqueness of a global positive solution are studied. By using the invariant measure theory and singular boundary theory of diffusion process, existence of stochastic Hopf bifurcation and stochastic stability are investigated. By constructing appropriate Lyapunov functions, asymptotic dynamic behavior of the proposed hybrid stochastic system with double time delays and Lévy jumps is discussed. Numerical simulations are provided to show consistency with theoretical analysis. (shrink)