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After a historical sketch of thedynamical hypothesis, we stress that it is a functionalist hypothesis. We then tackle the point of adynamical approach to constituent structures and emphasize thatdynamicalmodeling must be coupled with morphological analysis.

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We formulate a dynamic model of vascular tumor growth, in which the interdependence of vascular dynamics with tumor volume is considered. The model describes the angiogenic switch; thus the inhibition of the vascularization process by antiangiogenic drugs may be taken into account explicitly. We validate the model against volume measurement data originating from experiments on mice and analyze the model behavior assuming different inputs corresponding to different therapies. Furthermore, we show that a simple extension of the model is capable of (...) considering cytotoxic and antiangiogenic drugs as inputs simultaneously in qualitatively different ways. (shrink)

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A sequel to Global Trade Analysis:Modeling and Applications, this new volume presents the technical aspects of the Global Trade Analysis Program's global dynamic framework and its applications within important global policy issues. The book covers a diverse set of topics including trade reform, growth, investment, technology, demographic change and the environment. Environmental issues are particularly well-suited for analysis with GDyn, and this volume covers its uses with climate change, resource use and technological progress in agriculture. Other applications presented (...) in the book focus on integration issues such as rules governing foreign investment, e-commerce regulations, trade in services, harmonization of technical standards, sanitary and photo-sanitary regulations, streamlining of customs procedures, and demographic change and migration. (shrink)

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This paper concerns design thinking (Lawson, 1980), system thinking (systems theory) (von Bertalanffy, 1968), and system dynamicsmodeling as methodological platforms for analyzing large amounts of qualitative data and transforming it into quantitative mode. The aims of this article are to present an integral (mixed) research process including the design thinking process—a solution oriented approach applicable in the social sciences and humanities which enables to reveal causality in research on societal and behavioral issues. This integral approach is illustrated by (...) an empirical pilot study from art/design-educational environment. (shrink)

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Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamicmodeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamicmodeling is applied. There are many dynamicmodeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of (...) gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue. (shrink)

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Although its roots can be traced to the 19th century, progress in the study of nonlineardynamical systems has taken off in the last 30 years. While pertinent source material exists, it is strewn about the literature in mathematics, physics, biology, economics, and psychology at varying levels of accessibility. A compendium research methods reflecting the expertise of major contributors to NDS psychology, NonlinearDynamical Systems Analysis for the Behavioral Sciences Using Real Data examines the techniques proven to be (...) the most useful in the behavioral sciences. The editors have brought together constructive work on new practical examples of methods and application built on nonlinear dynamics. They cover dynamics such as attractors, bifurcations, chaos, fractals, catastrophes, self-organization, and related issues in time series analysis, stationarity,modeling and hypothesis testing, probability, and experimental design. The analytic techniques discussed include several variants of the fractal dimension, several types of entropy, phase-space and state-space diagrams, recurrence analysis, spatial fractal analysis, oscillation functions, polynomial and Marquardt nonlinear regression, Markov chains, and symbolic dynamics. The book outlines the analytic requirements faced by social scientists and how they differ from those of mathematicians and natural scientists. It includes chapters centered on theory and procedural explanations for running the analyses with pertinent examples and others that illustrate applications where a particular form of analysis is seen in the context of a research problem. This combination of approaches conveys theoretical and practical knowledge that helps you develop skill and expertise in framing hypotheses dynamically and building viable analytic models to test them. (shrink)

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We show how a simple nonlineardynamical system (the discrete quadratic iteration on the unit segment) can be the basis for modelling the embryogenesis process. Such an approach, even though being crude, can nevertheless prove to be useful when looking with the two main involved processes:i) on one hand the cell proliferation under successive divisions ii) on the other hand, the differentiation between cell lineages. We illustrate this new approach in the case of Caenorhabditis elegans by looking at the (...) early stages of embryogenesis, up to several hundreds of cells (lima bean larval stage). We show how the many results that have been obtained by several groups can be interpreted in terms of values for the parameters controlling thedynamical system. Furthermore, we can extend the model to the cases of genetic mutations. More precisely the teratogenetic and lethal effects are associated with abnormal variation of the control parameters with time. (shrink)

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The contents and structure of semantic memory have been the focus of much recent research, with major advances in the development of distributional models, which use word co‐occurrence information as a window into the semantics of language. In parallel, connectionistmodeling has extended our knowledge of the processes engaged in semantic activation. However, these two lines of investigation have rarely been brought together. Here, we describe a processing model based on distributional semantics in which activation spreads throughout a semantic (...) network, as dictated by the patterns of semantic similarity between words. We show that the activation profile of the network, measured at various time points, can successfully account for response times in lexical and semantic decision tasks, as well as for subjective concreteness and imageability ratings. We also show that the dynamics of the network is predictive of performance in relational semantic tasks, such as similarity/relatedness rating. Our results indicate that bringing together distributional semantic networks and spreading of activation provides a good fit to both automatic lexical processing (as indexed by lexical and semantic decisions) as well as more deliberate processing (as indexed by ratings), above and beyond what has been reported for previous models that take into account only similarity resulting from network structure. (shrink)

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The fundamental relations in private law are claims and duties. These legal relations can be changed by agents with the appropriate legal powers. We use propositional dynamic logic and ideas about propositional control from the agency literature to formalize these changes in legal relations. Our models are sets of states with functions specifying atomic facts, agents’ abilities to change atomic facts, legal relations between agents concerning changing atomic facts and agents’ powers. We present a formal language that allows us to (...) describe models and changes of models caused by two kinds of actions: actions that change atomic facts and actions that change legal relations. Next, we present a sound and complete calculus for this language. The paper demonstrates that the perspective on actions borrowed from computer science can be used to shed interesting light on the dynamics of legal relations. (shrink)

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This dissertation challenges two prevalent views on the topic of scientific explanation: that science explains by revealing causal mechanisms, and that science explains by unifying our knowledge of the world. ;My methodological strategy is to compare our best current philosophical accounts of scientific explanation with evidence from contemporary scientific research. In particular, I focus on evidence fromdynamical explanations, that is, explanations which appeal to nonlineardynamicalmodeling for their force. Nonlineardynamicalmodeling is a (...) type of mathematicalmodeling which is used by scientists in many different disciplines, including population biology, ecology, physics, and psychology. ;Chapter 1 argues thatdynamical explanations are a philosophically important class of explanations, based on their prevalence and their close relationship with the semantic view of theories. ;Chapters 2 and 3 conclude that extant causal and unification accounts encounter serious difficulties when applied todynamical explanations. Chapter 2 argues that causal relevance is neither a necessary nor a sufficient condition for explanatory relevance. Chapter 3 clarifies and evaluates different claims about the unifying power of science. Here, I argue thatdynamical explanations provide some support for the thesis that unification is constitutive of explanation. However,dynamical explanations also indicate that some of the intuitions embodied in extant unification accounts are untenable. ;Chapter 4 concludes by advancing diagnostic criticisms of existing causal and unification accounts. I explore the relationships betweendynamical explanations and three conceptions of scientific explanation, as well as the relationships between different types of inference and scientific understanding. I suggest that philosophers look to cognitive science and the semantic view of theories for aid in constructing a viable positive account of explanation. ;The technical appendix introduces several key definitions and concepts ofdynamical systems theory. (shrink)

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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)

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In the interwar years the Gran Paradiso ibex population followed two subsequent, contrasting trends: a steady rise once the national park was established in 1922, followed by a precipitous fall after the Fascist regime took direct control of conservation in 1934, which almost led to the colony’s extinction. This paper addresses the issue of how models taken from population ecology may inform historical narratives. The data for the interwar years were analyzed using a statistical model based on climate and population (...) density, which has proved reliable for most of the post-World War II period. The article highlights the pivotal role of anthropic variables in determining the inter-war trends and how these are best analyzed using historical scholarship. (shrink)

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Emerging parallel processing and increased flexibility during the acquisition of cognitive skills form a combination that is hard to reconcile with rule‐based models that often produce brittle behavior. Rule‐based models can exhibit these properties by adhering to 2 principles: that the model gradually learns task‐specific rules from instructions and experience, and that bottom‐up processing is used whenever possible. In a model of learning perfect time‐sharing in dual tasks (Schumacher et al., 2001), speedup learning and bottom‐up activation of instructions can explain (...) parallel behavior. In a model of a complex dynamic task (Carnegie Mellon University Aegis Simulation Program [CMU‐ASP], Anderson et al., 2004), parallel behavior is explained by the transition from serially organized instructions to rules that are activated by both top‐down (goal‐driven) and bottom‐up (perceptually driven) factors. Parallelism lets the model opportunistically reorder instructions, leading to the gradual emergence of new task strategies. (shrink)

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Dynamicism has provided cognitive science with important tools to understand some aspects of “how cognitive agents work” but the issue of “what makes something cognitive” has not been sufficiently addressed yet, and, we argue, the former will never be complete without the later. Behavioristic characterizations of cognitive properties are criticized in favor of an organizational approach focused on the internal dynamic relationships that constitute cognitive systems. A definition of cognition as adaptive-autonomy in the embodied and situated neurodynamic domain is provided: (...) the compensatory regulation of a web of stability dependencies between sensorimotor structures, is created and preserved during a historical/developmental process. We highlight the functional role of emotional embodiment: internal bioregulatory processes coupled to the formation and adaptive regulation of neurodynamic autonomy. Finally, we discuss a “minimally cognitive behavior program” in evolutionary simulation modelling suggesting that much is to be learned from a complementary “minimally cognitive organization program”. (shrink)

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Individuals make decisions under uncertainty every day. Decisions are based on in- complete information concerning the potential outcome or the predicted likelihood with which events occur. In addition, individuals’ choices often deviate from the rational or mathematically objective solution. Accordingly, the dynamics of human decision making are difficult to capture using conventional, linear mathematical models. Here, we present data from a 2-choice task with variable risk between sure loss and risky loss to illustrate how a simple nonlineardynamical system (...) can be employed to capture the dynamics of human decision making under uncertainty (i.e., multistability, bifurcations). We test the feasibility of this model quantitatively and demonstrate how the model can account for up to 86% of the observed choice behavior. The implications of usingdynamical models for explaining the nonlin- ear complexities of human decision making are discussed as well as the degree to which the theory of nonlineardynamical systems might offer an alternative framework for understanding human decision making processes. (shrink)

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The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are possible. These include the particle on an energy landscape, the potential landscape, and the Lyapunov function landscape. I discuss the dynamics that these representations admit, and the application of each to ecologicalmodeling and the analysis (...) and representation of stability. (shrink)

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I explain why, within the nonclassical framework for cognitive science we describe in the book, cognitive-state transitions can fail to be tractably computable even if they are subserved by a discretedynamical system whose mathematical-state transitions are tractably computable. I distinguish two ways that cognitive processing might conform to programmable rules in which all operations that apply to representation-level structure are primitive, and two corresponding constraints on models of cognition. Although Litch is correct in maintaining that classical cognitive science (...) is not committed to the first constraint, it is committed to the second. This fact constitutes an illuminating gloss on our claim that one foundational assumption of classicism is that human cognition conforms to programmable, representation-level, rules. (shrink)

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Mathematicalmodeling is a convenient way for characterization of complex ecosystems. This approach was applied to study the dynamics of zooplankton in Lake Sevan (Armenia) at different stages of anthropogenic eutrophication with the use of a novel method called discretemodeling ofdynamical systems with feedback (DMDS). Simulation demonstrated that the application of this method helps in characterization of inter- and intra-component relationships in a natural ecosystem. This method describes all possible pairwise inter-component relationships like “plus–plus,” “minus–minus,” (...) “plus–minus,” “plus–zero,” “minus–zero,” and “zero–zero” that occur in most ecosystems. Based on the results, a working hypothesis was formulated. It was found that the sensitivity to weak external influence in zooplanktons was the greatest during the mid period of eutrophication in Lake Sevan, whereas in the final stages of eutrophication, an outbreak in the biomass production of cyanobacteria was evident. To support this approach, a weak external disturbance in the form of magnetic storm was used to see its effect on species Daphnia longispina sevanica. A statistically significant correlation between the frequency of magnetic storms and the number of this species was revealed and an increase in the number of toxic cyanobacteria species as a consequence of eutrophication. This paper, for the first time, suggests a DMDS method, to diagnose impact of anthropogenic eutrophication on environment. (shrink)

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Dynamic Epistemic Logic is claimed to be a dynamic version of epistemic logic. While this being true, there are severaldynamical aspects that cannot be reasoned about in Dynamic Epistemic Logic. When a scenario is fixed and a possible world model representing the scenario is constructed, the possible future ways the system can evolve are in some sense already determined. For instance no new agents can enter the scenario and no new propositional facts can become relevant. Thismodeling (...) perspective is the main motivation for the partial version of Dynamic Epistemic Logic introduced in this paper, which in particular, allows for the set of agents and the set of propositional variables to change. (shrink)

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Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computationalmodeling is a major tool for understanding these mechanisms. The particular approaches to computationalmodeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction (...) with their styles ofmodeling. In particular, mental operations often are conceptualized as comparable to the processes employed in classical symbolic AI or neural network models. These models, in turn, have been interpreted by some as themselves intelligent systems since they employ the same type of operations as does the mind. For this paper, what is significant about these approaches tomodeling is that they are constructed specifically to account for behavior and are evaluated by how well they do so—not by independent evidence that they describe actual operations in mental mechanisms. (shrink)

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The current article aims to provide an up-to-date synopsis of available techniques to study affect dynamics using intensive longitudinal data (ILD). We do so by introducing the following eight dichotomies that help elucidate what kind of data one has, what process aspects are of interest, and what research questions are being considered: (1) single- versus multiple-person data; (2) univariate versus multivariate models; (3) stationary versus nonstationary models; (4) linear versus nonlinear models; (5) discrete time versus continuous time models; (6) discrete (...) versus continuous variables; (7) time versus frequency domain; and (8)modeling the process versus computing descriptives. In addition, we discuss what we believe to be the most urging future challenges regarding themodeling of affect dynamics. (shrink)

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Recent computational models of perception conceptualize auditory oddball responses as signatures of a learning process, in line with the influential view of the mismatch negativity as a prediction error signal. Novel MMN experimental paradigms have put an emphasis on neurophysiological effects of manipulating regularity and predictability in sound sequences. This raises the question of the contextual adaptation of the learning process itself, which on the computational side speaks to the mechanisms of gain-modulated prediction error. In this study using electrocorticographic signals, (...) we manipulated the predictability of oddball sound sequences with two objectives: Uncovering the computational process underlying trial-by-trial variations of the cortical responses. The fluctuations between trials, generally ignored by approaches based on averaged evoked responses, should reflect the learning involved. We used a general linear model and Bayesian Model Reduction to assess the respective contributions of experimental manipulations and learning mechanisms under probabilistic assumptions. To validate and expand on previous findings regarding the effect of changes in predictability using simultaneous EEG-MEG recordings. Our trial-by-trial analysis revealed only a few stimulus-responsive sensors but the measured effects appear to be consistent over subjects in both time and space. In time, they occur at the typical latency of the MMN. In space, we found a dissociation between time-independent effects in more anterior temporal locations and time-dependent effects in more posterior locations. However, we could not observe any clear and reliable effect of our manipulation of predictability modulation onto the above learning process. Overall, these findings clearly demonstrate the potential of trial-to-trialmodeling to unravel perceptual learning processes and their neurophysiological counterparts. (shrink)

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How individuals tend to evaluate the combination of their own and other’s payoffs—social value orientations—is likely to be a potential target of future moral enhancers. However, the stability of cooperation in human societies has been buttressed by evolved mildly prosocial orientations. If they could be changed, would this destabilize the cooperative structure of society? We simulate a model of moral enhancement in which agents play games with each other and can enhance their orientations based on maximizing personal satisfaction. We find (...) that given the assumption that very low payoffs lead agents to be removed from the population, there is a broadly stable prosocial attractor state. However, the balance between prosociality and individual payoff-maximization is affected by different factors. Agents maximizing their own satisfaction can produce emergent shifts in society that reduce everybody’s satisfaction. Moral enhancement considerations should take the issues of social emergence into account. (shrink)

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Recently, it has been provocatively claimed thatdynamicalmodeling approaches signal the emergence of a new explanatory framework distinct from that of mechanistic explanation. This paper rejects this proposal and argues thatdynamical explanations are fully compatible with, even naturally construed as, instances of mechanistic explanations. Specifically, it is argued that the mathematical framework of dynamics provides a powerful descriptive scheme for revealing temporal features of activities in mechanisms and plays an explanatory role to the extent it (...) is deployed for this purpose. It is also suggested that more attention should be paid to the distinctive methodological contributions of thedynamical framework including its usefulness as a heuristic for mechanism discovery and hypothesis generation in contemporary neuroscience and biology. (shrink)

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We analyze different aspects of our quantummodeling approach of human concepts and, more specifically, focus on the quantum effects of contextuality, interference, entanglement, and emergence, illustrating how each of them makes its appearance in specific situations of the dynamics of human concepts and their combinations. We point out the relation of our approach, which is based on an ontology of a concept as an entity in a state changing under influence of a context, with the main traditional concept (...) theories, that is, prototype theory, exemplar theory, and theory theory. We ponder about the question why quantum theory performs so well in itsmodeling of human concepts, and we shed light on this question by analyzing the role of complex amplitudes, showing how they allow to describe interference in the statistics of measurement outcomes, while in the traditional theories statistics of outcomes originates in classical probability weights, without the possibility of interference. The relevance of complex numbers, the appearance of entanglement, and the role of Fock space in explaining contextual emergence, all as unique features of the quantummodeling, are explicitly revealed in this article by analyzing human concepts and their dynamics. (shrink)

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The purpose of this article is to extend from the business and society research focus on corporate political strategy and to factor this emphasis into business strategy thinking. The approach taken is to incorporate business and society concepts into a model that parallels Michael Porter's well-known Five Forces Model of business strategy. The applicability of the parallel model for practitioners and academics is then illustrated by using the model to analyze the television violence issue.

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This paper proposes a new robotic fish which avoids the complex mechanical structure and reduces the model complexity comparing to the existing bioinspired robotic fish, giving rise to a semibiomimetic robotic fish. The generalized Lagrange equation is adopted to establish the dynamic model of the robotic fish. The controllability of the system is analyzed, upon which a trajectory tracking control algorithm is designed by using the feedback linearization technique. The simulation results show that the dynamic model adopted in this paper (...) can achieve better control performance. (shrink)

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The state-of-art research in the field of life’s organization confronts the need to investigate a number of interacting components, their properties and conditions of sustainable behaviour within a natural system. In biology, ecology and life sciences, the performance of such stable system is usually related to homeostasis, a property of the system to actively regulate its state within a certain allowable limits. In our previous work, we proposed a deterministic model for systems’ homeostasis. The model was based ondynamical (...) system’s theory and pairwise relationships of competition, amensalism and antagonism taken from theoretical biology and ecology. However, the present paper proposes a different dimension to our previous results based on the same model. In this paper, we introduce the influence of inter-component relationships in a system, wherein the impact is characterized by direction (neutral, positive, or negative) as well as its (absolute) value, or strength. This makes the model stochastic which, in our opinion, is more consistent with real-world elements affected by various random factors. The case study includes two examples from areas of hydrobiology and medicine. The models acquired for these cases enabled us to propose a convincing explanation for corresponding phenomena identified by different types of natural systems. (shrink)

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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)

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Comparativemodeling is necessary for semiotic inquiry. To better theorize such pursuits, a reflexive turn is in order: comparativemodeling needs comparativemodeling. In search of experientially grounded analogies better suited for understanding, validating, scrutinizing, and accounting for the situation of the semiotic inquirer, this paper applies insights from Peircean process semiotics and Göran Sonesson’s extended theory of cultural semiotics toward two ends: one theoretical, the other applied. First, I undertake a critical review of recent scholarly and (...) creative works that attempt to adapt concepts of “parallax” as a source domain for comparativemodeling activities. I do this in order to continue laying groundwork for a more complex, systematic theory of reflexive semioticmodeling in human inquiry, building on my earlier work. Second, I explore a specific case study of comparative interculturalmodeling: namely, nationalist ethnic classification strategies in China and Vietnam. While many researchers have considered the onomastic and geopolitical dimensions of state-sanctioned ethnic categorization programs in these two countries, little has been done to unpack the powerful visual and narratological strategies employed by both; and little has been done to compare the intercultural categories these strategies serve to legitimize. The Vietnamese classification program is clearly modeled on its Chinese counterpart historically, but important categorical mismatches emerge between the two that indicate the presence of hidden diversity. Comparing the two systems also leads to a number of discoveries with implications for further developing the theory of cultural semiotics. Ultimately, the function or purpose of parallaxmodeling is shown to both comprehend and point beyond nascent intercultural and intracultural models toward more complex blends, by holding all such relations in a comparative frame, not as irreconcilable positions but as a more developed composite sign indicating the presence of yet more deeply buried dynamic objects to be searched out through further collateral experience. (shrink)

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Dynamic epistemic logic, broadly conceived, is the study of logics of information change. This is the first paper in a two-part series introducing this research area. In this paper, I introduce the basic logical systems for reasoning about the knowledge and beliefs of a group of agents.

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