The COVID-19 pandemic has caused major changes in the psychological capital structure of individuals and groups, especially among members of the upper echelons of Chinese mixed-ownership reform enterprises, who are more sensitive to the environment. Based on prospect theory. In order to further study the changes in the psychological capital structure of upper echelons of the mixed ownership reform of state-owned enterprises under the influence of the COVID-19, and what impact it has on the decision-making behavior of the upper echelons (...) and the development performance of the mixed ownership reform enterprises, this paper introduces the system dynamics research method into the research field of the upper echelons for the first time, and studies the psychological capital structure of the upper echelons through simulation. This paper puts forward new research ideas for the research on the psychological capital structure of upper echelons. Using the system dynamics method, this study investigates the changes induced by the COVID-19 pandemic, on the psychological capital structure of the upper echelons of Chinese mixed-ownership reform enterprises; and assesses the concept model of behavioral psychological capital adjustment. The impact of COVID-19 on communication strategies among upper echelons, directly affects the evolution results of the decision-making system. The psychological capital structure in the upper echelons has evolutionary stability strategies in three cases. In some cases, the system evolution presents periodic characteristics. The higher the probability of group communication, the more stable the psychological capital structure, and the greater the fluctuation of behavioral integration. There is a significant correlation between the level of efficacy and resilience of upper echelons psychological capital structure and upper echelons decision-making behavior. Under the condition of improving the communication probability among upper echelon members, there is a positive correlation between the level of hope and optimism of upper echelon and the power structure of upper echelon and the development performance of mixed reform enterprises. Develop the psychological capital structure of upper echelon of mixed reform enterprises, improve the level of financing development decision-making ability and improve decision-making performance. (shrink)

Having entered into the problem structuring methods, system dynamics (SD) is an approach, among systems’ methodologies, which claims to recognize the main structures of socio-economic behaviors. However, the concern for building or discovering strong philosophical underpinnings of SD, undoubtedly playing an important role in the modeling process, is a long-standing issue, in a way that there is a considerable debate about the assumptions or the philosophical foundations of it. In this paper, with a new perspective, we have explored (...) theory of knowledge in SD models and found strange similarities between classic epistemological concepts such as justification and truth, and the mechanism of obtaining knowledge in SD models. In this regard, we have discussed related theories of epistemology and based on this analysis, have suggested some implications for moderating common problems in the modeling process of SD. Furthermore, this research could be considered a reword of system dynamics modeling principles in terms of theory of knowledge. (shrink)

To improve the problems of inconvenient communication in the manufacturing industry, the ineffective use of resources, and the inability to efficiently complete manufacturing tasks, resource sharing has become an important model to promote the transformation and upgrading of the manufacturing industry. We used multiagent modeling to construct a resource-sharing model and take Baosteel as the micro background and the manufacturing industry as the macro background. Under this model, we discovered the effect of resource sharing on the efficiency of intelligent manufacturing (...) under network collaboration through system dynamics research. We built and simulated a dynamic model of system dynamics that couples the two backgrounds and have given policy suggestions according to the simulation result. (shrink)

Financial risks are among the most important risks in the construction industry projects, which significantly impact project objectives, including project cost. Besides, financial risks have many interactions with each other and project parameters, which must be taken into account to analyze risks correctly. In addition, a source of financial risks in a project is the contract, which is the most important project document. Identifying terms related to financial risks in a contract and considering their effects on the risk management process (...) is an essential issue that has been neglected. Hence, an integrated model for evaluating financial risks and their related contractual clauses were presented. To this end, the effect of financial risks on the project cost was simulated using a system dynamics model. Moreover, terms related to financial risks in a contract text were identified and extracted using text mining, and their effect was included in the system dynamics model. The model was implemented in a hospital construction project in Tehran as a case study, and its results were analyzed. The innovation of the research is integrating text mining and the system dynamics model to investigate the effect of financial risks and related contractual clauses on the project cost. (shrink)

This paper concerns design thinking (Lawson, 1980), system thinking (systems theory) (von Bertalanffy, 1968), and system dynamics modeling 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)

The contradictions between food poverty affecting a large section of the global population and the everyday wastage of food, particularly in high income countries, have raised significant academic and public attention. All actors in the food chain have a role to play in food waste prevention and reduction, including farmers, food manufacturers and processors, caterers and retailers and ultimately consumers. Food surplus redistribution is considered by many as a partial solution to food waste reduction and food poverty mitigation, while others (...) criticize charitable initiatives as inadequate responses, that inhibit governments from responsibly protecting the citizens right to food. This paper frames food assistance as “hybrid systems”, situating at the intersection of territorial food, public welfare and third sector voluntary systems. Based on available literature and reflections on previous research examining food banks in Italy, we develop a system dynamics conceptual mapping. The aim is to model a set of relations and dynamic mechanisms associated with variables relevant to food waste generation, food recovery for social purposes and food poverty alleviation. The analysis of feedback interactions highlights the vulnerabilities of food assistance systems that occur when addressing food poverty by reducing food surplus. In summary, as the awareness on food poverty and food surplus arises, incentives to food recovery and redistribution strengthen the role of food assistance actors, increasing their exposure to drivers of change, such as retailers’ standards for food surplus prevention. This paper contributes to the current academic debate on charitable food assistance, with insights for policy makers and other systems’ actors. (shrink)

Consequentialism is a moral philosophy that maintains that the moral worth of an action is determined by the consequences it has for the welfare of a society. Consequences of model design are a part of the model lifecycle that is often neglected. This paper investigates the issue using system dynamics modeling as an example. Since a system dynamics model is a product of the modeler’s design decisions, the modeler should consider the life cycle consequences of using (...) the model. Seen from a consequentialist perspective, the consequences of policies developed from system dynamics models determine the model’s moral value. This concept is explored by discussing model uncertainty from an engineering perspective. In this perspective, the ethical considerations shift from the behavior of the modeler to the model itself and the model’s inherent uncertainty. When the ethical considerations are taken away from the modeler and directed to what the model does, the ethical boundaries extend beyond the proximity of the model. This discussion renews the ethics conversation in system dynamics by considering this shift in philosophical perspective, and investigates how consequentialist moral philosophy applies to the modeling process and in communicating with decision-makers. A model of social assistance in Norway in the context of immigration pressures illustrates some possibilities for addressing these ethical concerns. This paper argues for an ethical framework, or at the very least, an ethical conversation within the field of system dynamics.Article first published online: 25 FEB 2017. (shrink)

James Madison University Harrisonburg, VA 22807 USA Tel: 001-540-568-3212 Fax: 001-540-568-3010 Email: rosserjb@jmu.edu..

Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin’s theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it (...) incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself. (shrink)

From birth to 15 months infants and caregivers form a fundamentally intersubjective, dyadic unit within which the infant’s ability to recognize gender/sex in the world develops. Between about 18 and 36 months the infant accumulates an increasingly clear and subjective sense of self as female or male. We know little about how the precursors to gender/sex identity form during the intersubjective period, nor how they transform into an independent sense of self by 3 years of age. In this Theory and (...) Hypothesis article I offer a general framework for thinking about this problem. I propose that through repetition and patterning, the dyadic interactions in which infants and caregivers engage imbue the infant with an embodied, i.e., sensori-motor understanding of gender/sex. During this developmental period (which I label Phase 1) gender/sex is primarily an intersubjective project. From 15 to 18 months (which I label Phase 2) there are few reports of newly appearing gender/sex behavioral differences, and I hypothesize that this absence reflects a period of developmental instability during which there is a transition from gender/sex as primarily inter-subjective to gender/sex as primarily subjective. Beginning at 18 months (i.e., the start of Phase 3), a toddler’s subjective sense of self as having a gender/sex emerges, and it solidifies by 3 years of age. I propose a dynamic systems perspective to track how infants first assimilate gender/sex information during the intersubjective period (birth to 15 months); then explore what changes might occur during a hypothesized phase transition (15 to 18 months), and finally, review the emergence and initial stabilization of individual subjectivity-the period from 18 to 36 months. The critical questions explored focus on how to model and translate data from very different experimental disciplines, especially neuroscience, physiology, developmental psychology and cognitive development. I close by proposing the formation of a research consortium on gender/sex development during the first 3 years after birth. (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)

This article illustrates the important scientific role that a systems approach might play within the social sciences and humanities, above all through its contribution to a common language, shared conceptualizations, and theoretical integration in the face of the extreme (and growing) fragmentation among the social sciences (and between the social sciences and the natural sciences). The article outlines a systems theoretic approach, actor-system-dynamics (ASD), whose authors have strived to re-establish systems theorizing in the social sciences (after a period (...) of marginalization since the late 1960s). This is done, in part, by showing how key social science concepts are readily incorporated and applied in social system analysis. (shrink)

The spread of epidemics, especially COVID-19, is having a significant impact on the world. If an epidemic is not properly controlled at the beginning, it is likely to spread rapidly and widely through the coexistence relationship between natural and social systems. A university community is a special, micro-self-organized social system that is densely populated. However, university authorities in such an environment seem to be less cautious in the defence of an epidemic. Currently, there is almost no quantitative research on (...) epidemic spreading and response strategies in universities. In this paper, a case study of a university community is considered for a simulation of an infection evolving after an epidemic outbreak based on the method of system dynamics of the three stages. The results show the following: By improving the speed of the initial emergency response, the total number of patients can be effectively controlled. A quarantine policy helps to slow down the evolution of infection. The higher the isolation ratio, the higher the cost; therefore, the isolation ratio should be optimized. It is important to make emergency plans for controlling epidemic spreading and carry out emergency drills and assessments regularly. According to the results of this study, we suggest an emergency management framework for public health events in university communities. (shrink)

The academic literature has viewed drivers of corruption in isolation and, consequently, failed to examine their synergistic effect. Such an isolated view provides incomplete information, leads to a misleading conclusion, and causes great difficulty in curbing corruption. This paper conducts a systematic literature review to identify the drivers of corruption in the construction industry. Subsequently, it develops a system dynamics (SD) model by conceptualizing corruption as a complex system of interacting drivers. Building on stakeholder and open systems (...) theories, the proposed SD model shows how the complex reinforcing relationship between authoritative, organizational, cultural, and financial drivers of corruption further increases corrupt practices. The new model also provides lessons that can be helpful in the development of policy frameworks to control corruption in the construction industry. To achieve success in the fight against corruption, the findings of this research suggest that (1) corruption must be understood at both the organizational and state levels, (2) anticorruption practices must be informed by ethically grounded stakeholder management strategies, and (3) anticorruption reforms must go hand-in-hand with strategies to tackle the economic downturn. (shrink)

We propose an analysis of the notion of model as crucially related to the notion of point of view. A model in this sense would always suggest a certain way of looking at a real system, a certain way of thinking about it and a certain way of acting upon it. We focus on System Dynamics as a paradigmatic case with respect to many of the features and problems we can find in the field of modelling and (...) simulation. We analyse in detail some of those features. All of them would be present in many other cases of construction and use of models. Furthermore, they would support the thesis that a model can be fruitfully understood as offering a point of view capable of improving our own points of view over a certain system. The point of view offered by the model could include both non-conceptual and conceptual contents, it would have a complex structure and behaviour, and it would have direct consequences on the decisions made by the subjects adopting that point of view. (shrink)

In the current social media environment, emotional branding communication has become a common marketing tool for brand owners, and therefore it has become particularly important and urgent to study it. Based on the perspective of brand equity theory, combined with the new characteristics of marketing communication in the social media environment, this paper constructed an emotional branding communication model in the social media environment. The system dynamics method was used to simulate and analyze the new product marketing (...) class='Hi'>system to assess whether it could stir the emotional needs of the consumers and resonate within their hearts. This paper discusses the asymmetric communication of different brands regarding the same commodity to determine the impact of this exchange mechanism, that is, only the weak brands in the market initially adopt marketing methods, while the strong brands do not participate in social marketing activities. It was found that the influence of marketing frequency and marketing intensity on symmetric and asymmetric communications was different. In the face of different types of competitors, the marketing strategy of weak brands needs emphasis. Through unit consistency test, structure verification test, effectiveness, and rationality test, it was proven that the emotional branding communication model and new product sales interaction simulation model established in this paper were reasonable and effective. (shrink)

In dynamic system control, cognitive mechanisms and abilities underlying performance may vary depending on the nature of the task. We therefore investigated the effects of system structure and its interaction with cognitive abilities on system control performance. A sample of 127 university students completed a series of different system control tasks that were manipulated in terms of system size and recurrent feedback, either with or without a cognitive load manipulation. Cognitive abilities assessed included reasoning ability, (...) working memory capacity, and cognitive reflection. System size and recurrent feedback affected overall performance as expected. Overall, the results support that cognitive ability is a good predictor of performance in dynamic system control tasks but predictiveness is reduced when the system structure contains recurrent feedback. We discuss this finding from a cognitive processing perspective as well as its implications for individual differences research in dynamic systems. (shrink)

With the advent of computers in the experimental labs, dynamic systems have become a new tool for research on problem solving and decision making. A short review of this research is given and the main features of these systems (connectivity and dynamics) are illustrated. To allow systematic approaches to the influential variables in this area, two formal frameworks (linear structural equations and finite state automata) are presented. Besides the formal background, the article sets out how the task demands of (...) system identification and system control can be realised in these environments, and how psychometrically acceptable dependent variables can be derived. (shrink)

Scientists often think of the world as a dynamical system, a stochastic process, or a generalization of such a system. Prominent examples of systems are the system of planets orbiting the sun or any other classical mechanical system, a hydrogen atom or any other quantum–mechanical system, and the earth’s atmosphere or any other statistical mechanical system. We introduce a general and unified framework for describing such systems and show how it can be used to (...) examine some familiar philosophical questions, including the following: how can we define nomological possibility, necessity, determinism, and indeterminism; what are symmetries and laws; what regularities must a system display to make scientific inference possible; how might principles of parsimony such as Occam’s Razor help when we make such inferences; what is the role of space and time in a system; and might they be emergent features? Our framework is intended to serve as a toolbox for the formal analysis of systems that is applicable in several areas of philosophy. (shrink)

Open peer commentary on the article “A Cybernetic Computational Model for Learning and Skill Acquisition” by Bernard Scott & Abhinav Bansal. Upshot: The target paper acknowledges some early computer modelling that I did in the years 1966–1968 when working with Pask at System Research Ltd in Richmond. In the commentary, I revisit the roots of this kind of modelling and follow the trajectory from then to today’s growing understanding of the dynamics of cognitive systems.

Exploring the dynamics feature of robust chaotic system is an attractive yet recent topic of interest. In this paper, we introduce a three-dimensional fractional-order chaotic system. The important finding by analysis is that the position of signalx3descends at the speed of 1/cas the parameterbincreases, and the signal amplitude ofx1,x2can be controlled by the parametermin terms of the power function with the index −1/2. What is more, the dynamics remains constant with the variation of parametersbandm. Consequently, this (...) system can provide rich encoding keys for chaotic communication. By considering the properties of amplitude and position modulation, the partial projective synchronization and partial phase synchronization are realized with linear control scheme. The distribution map of optimal synchronization region in the control-parameter space is charted by defining the power consumption of controller. Numerical simulations are executed to confirm the theoretical analysis. (shrink)

The dynamics of neural populations capture the laws of the mindThis paper focuses on the level of neural networks. Examining the case of recurrent neural networks, the paper argues that the dynamics of neural populations form a privileged level of explanation in cognitive science. According to Schöner, this level is privileged, because it enables cognitive scientists to discover the laws governing organisms’ cognition and behaviour.

Dynamical systems theory (DST) is a branch of mathematics that assesses abstract or physical systems that change over time. It has a quantitative part (mathematical equations) and a related qualitative part (plotting equations in a state space). Nonlinear dynamical systems theory applies the same tools in research involving phenomena such as chaos and hysteresis. These approaches have provided different ways of investigating and understanding cognitive systems in cognitive science and neuroscience. The ‘dynamical hypothesis’ claims that cognition is and can be (...) understood as dynamical systems. Common consequences for such an approach include rejecting understanding cognition as information processing in nature, including eschewing explanatory roles for computation or representation. Contemporary applications of DST include mouse‐tracking studies in cognitive science and nonrepresentational perspectives on motor control in neuroscience. Such work has philosophical implications concerning the boundaries of cognition, explanation, and representations. DST offers powerful methodology and theories that raise many topics of philosophical significance. (shrink)

Dynamical systems are mathematical structures whose aim is to describe the evolution of an arbitrary deterministic system through time, which is typically modeled as (a subset of) the integers or the real numbers. We show that it is possible to generalize the standard notion of a dynamical system, so that its time dimension is only required to possess the algebraic structure of a monoid: first, we endow any dynamical system with an associated graph and, second, we prove (...) that such a graph is a category if and only if the time model of the dynamical system is a monoid. In addition, we show that the general notion of a dynamical system allows us not only to define a family of meaningful dynamical concepts, but also to distinguish among a cluster of otherwise tangled notions of reversibility, whose logical relationships are finally analyzed. (shrink)

Dynamic Topological Logic ( ) is a modal logic which combines spatial and temporal modalities for reasoning about dynamic topological systems , which are pairs consisting of a topological space X and a continuous function f : X → X . The function f is seen as a change in one unit of time; within one can model the long-term behavior of such systems as f is iterated. One class of dynamic topological systems where the long-term behavior of f is (...) particularly interesting is that of minimal systems ; these are dynamic topological systems which admit no proper, closed, f -invariant subsystems. In such systems the orbit of every point is dense, which within translates into a non-trivial interaction between spatial and temporal modalities. This interaction, however, turns out to make the logic simpler, and while s in general tend to be undecidable, interpreted over minimal systems we obtain decidability, although not in primitive recursive time; this is the main result that we prove in this paper. We also show that interpreted over minimal systems is incomplete for interpretations on relational Kripke frames and hence does not have the finite model property; however it does have a finite non-deterministic quasimodel property. Finally, we give a set of formulas of which characterizes the class of minimal systems within the class of dynamic topological systems, although we do not offer a full axiomatization for the logic. (shrink)

We show how a simple nonlinear dynamical 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 the dynamical 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)

In this article, the dynamical behaviors of two classes of chaotic systems are considered based on generalized Lyapunov function theorem with integral inequalities. Explicit estimations of the ultimate bounds are derived. The results presented in this article contain the existing results as special cases. Computer simulation results show that the proposed method is effective. © 2014 Wiley Periodicals, Inc. Complexity 21: 363–369, 2015.

A dynamic domain consists of a set of legal states and a transition function that maps states to states. AI formalisms for specifying dynamic domains have so far focused on describing the effects of actions, that is, the transition functions. In this paper we propose a notion of characteristic set of position systems for the purpose of describing legal states. A position system for a type of objects is a set of properties that are mutually exclusive, and that in (...) each state, every object of the type must satisfy exactly one of these properties called its position under the position system. A set of position systems, one for each type of objects in the domain, is characteristic if there is a one-to-one mapping between legal states and sets of objects’ positions under these position systems. These position systems are useful for reasoning about these dynamic systems including planning. In particular, we show that once we have characteristic sets of position systems for a dynamic domain, planning can be done by writing rules about when to move objects from one position to another. (shrink)

In this paper, a 3D jerk chaotic system with hidden attractor was explored, and the dissipativity, equilibrium, and stability of this system were investigated. The attractor types, Lyapunov exponents, and Poincare section of the system under different parameters were analyzed. Additionally, a circuit was carried out, and a good similarity between the circuit experimental results and the theoretical analysis testifies the feasibility and practicality of the original system. Furthermore, a robust feedback controller was designed based on (...) the finite-time stability theory, which guarantees the synchronization of 3D jerk master-slave system in finite time and asymptotically converges to the origin. Finally, we also give verification for the discussion in this paper by numerical simulation. (shrink)

We define a mathematical formalism based on the concept of an ‘‘open dynamical system” and show how it can be used to model embodied cognition. This formalism extends classical dynamical systems theory by distinguishing a ‘‘total system’’ (which models an agent in an environment) and an ‘‘agent system’’ (which models an agent by itself), and it includes tools for analyzing the collections of overlapping paths that occur in an embedded agent's state space. To illustrate the way this (...) formalism can be applied, several neural network models are embedded in a simple model environment. Such phenomena as masking, perceptual ambiguity, and priming are then observed. We also use this formalism to reinterpret examples from the embodiment literature, arguing that it provides for a more thorough analysis of the relevant phenomena. (shrink)

Dynamic topological logic provides a context for studying the confluence of the topological semantics for S4, topological dynamics, and temporal logic. The topological semantics for S4 is based on topological spaces rather than Kripke frames. In this semantics, □ is interpreted as topological interior. Thus S4 can be understood as the logic of topological spaces, and □ can be understood as a topological modality. Topological dynamics studies the asymptotic properties of continuous maps on topological spaces. Let a dynamic (...) topological system be a topological space X together with a continuous function f. f can be thought of in temporal terms, moving the points of the topological space from one moment to the next. Dynamic topological logics are the logics of dynamic topological systems, just as S4 is the logic of topological spaces. Dynamic topological logics are defined for a trimodal language with an S4-ish topological modality □, and two temporal modalities, ○ and *, both interpreted using the continuous function f. In particular, ○ expresses f’s action on X from one moment to the next, and * expresses the asymptotic behaviour of f. (shrink)

Logic is breaking out of the confines of the single-agent static paradigm that has been implicit in all formal systems until recent times. We sketch some recent developments that take logic as an account of information-driven interaction. These two features, the dynamic and the social, throw fresh light on many issues within logic and its connections with other areas, such as epistemology and game theory.

The Gestalt Bubble model describes a subjective phenomenal experience (what is seen) without taking into account the extraphenomenal constraints of perceptual experience (why it is seen as it is). If it intends to be an explanatory model, then it has to include either stimulus or neural constraints, or both.

Dynamical systems theory (DST) is gaining popularity in cognitive science and philosophy of mind. Recently several authors (e.g. J.A.S. Kelso, 1995; A. Juarrero, 1999; F. Varela and E. Thompson, 2001) offered a DST approach to mental causation as an alternative for models of mental causation in the line of Jaegwon Kim (e.g. 1998). They claim that some dynamical systems exhibit a form of global to local determination or downward causation in that the large-scale, global activity of the system governs (...) or constrains local interactions. This form of downward causation is the key to the DST model of mental causation. In this paper I evaluate the DST approach to mental causation. I will argue that the main problem for current DST approaches to mental causation is that they lack a clear metaphysics. I propose one metaphysical framework (Gillett, 2002a/b/c) that might deal with this deficiency. (shrink)

This paper explores some of the insights offered by a dynamic systems approach into the nature habits. “Dynamic systems approach” is used here as an umbrella term for studies of cognition, behavior, or development as systems of elements that change over time (e.g. Thelen and Smith 1994, 2006), while “dynamical systems” is reserved for studies that use differential equations to describe time-based systems (e.g., Schöner and Kelso 1988, Tschacher and Dauwalder 2003). The following discussion draws primarily from the coordination (...) class='Hi'>dynamics research of J.A. Scott Kelso (1995, 2012), which stems from Hermann Haken’s theory of synergetics (1977, 2003). However, the view of habits presented here is more of an interpretive application than a literature review, as the work on which it draws does not address habits explicitly. Perhaps this is because conventional notions of habit are too broad and loose to be captured succinctly in dynamic terms. Dynamical studies of human behavior have focused on more specific capacities such as motor coordination (Thelen et al. 1987), perception (Tuller et al. 1994), and learning (Kostrubiec et al. 2012). Yet this variety of applications suggests that the scope of the dynamic approach overlaps significantly with the domain of habits, so that dynamic concepts could be used to challenge and refine our conventional notions of habitual behavior. Accordingly, the goal of this paper is to raise questions about the nature of habits rather than present a comprehensive scientific theory. For a dynamic systems approach, stability is “the central concept” (Schöner and Kelso 1988, 1515). The “essential issues are the stability of the system, as indexed by the behavior of some collective measure of the multiple components, and the changes in stability over time” (Thelen and Smith 2006, 289). Intuitively, it would seem that the characteristic stability or stabilities of a system—its preferred states—are its habits. But the connection between stable states and habitual behavior is not as straightforward as it appears. The preferred states of a dynamic system are not simply “built in”; rather they depend on the interactive dynamics of the system’s components as well as the interactive couplings of the system with its environment. The following discussion explores the implications of four features of dynamic system stability for our understanding of habit: 1) stability is relative to timescale, and system stabilities at different timescales are interdependent; 2) the attractor landscape describing the characteristic stabilities of a system can be altered by various control parameters, including situational parameters; 3) systems can have multiple stabilities, such that the stability they exhibit at any given time may depend on their recent history; 4) learning processes tend to affect a whole cluster of interrelated stabilities and not just one stability in isolation. In light of these features of dynamic stability, it seems that there is no straightforward way to map conventional notions of personal habits onto stabilities of the human person considered as a nested dynamic system of body, brain, and environment (Chiel and Beer 1997). Should we consider as habits only the “intrinsic” stabilities of brain and body, regardless of the variety of behaviors that can arise from these stabilities in different situations? Or should only consider as habits those patterns of behavior that are regularly observed within a certain type of situation, regardless of how differently these patterns might be assembled at the body-brain level? From the dynamic perspective, stability and change are ubiquitous features at every level or spatiotemporal scale of description. Thus it seems arbitrary to apply the term “habit” only to one kind or level of stability, and perhaps this explains why the term is seldom used in dynamic systems literature. Yet it could be argued that this multilevel complexity is an advantage, as it can be used to challenge conventional notions of habit in interesting ways. Let us suppose that for any level of human behavior that can be described as a dynamic system, the stabilities or preferred states of that system—its “attractor landscape”—are at least analogous to habits, and should be considered as such. What is revealed by this broader, dynamic perspective?First, this view calls into question the usual timescale of habits, which is typically restricted to stable features of personality and behavior on the timescale of months or years (Lewis 2000). From a dynamic perspective, these stabilities are in principle no different from stabilities at faster and slower timescales. Moreover, different timescales of stability are interrelated: while the habits of any given timescale are shaped by the “deeper” habits of a slower timescale, they also can lead to changes at this deeper level. In other words, the “force of habit” is not one-way: habits are shaped by the behaviors that they themselves constrain. For example, mood is shaped by habits of personality, while a string of similar moods can lead to changes of personality. And though it may seem strange to think of moods as temporary emotional habits on the timescale of hours or days, their way of shaping and being shaped by emotional states on the timescale of seconds or minutes is analogous to the relationship between personality and mood. Likewise one can treat emotional states as habits that contribute to the attractor landscapes for thoughts and sensorimotor activity at an even faster timescale, while personality itself can be seen as evolving over the very “deep” landscape of developmental habits (Thelen and Smith 2006). Thus a dynamic view opens up a wider range of timescales across which the concept of habit might apply. But more importantly, even if we choose to restrict habit to just one of these levels, the interaction of timescales suggests that our understanding of any one level should draw upon at least two neighboring levels (Kelso 1995), if not the entire nested system. Second, a dynamic view of habit will include regular variations of the attractor landscape that occur in relation to changing parameters. In some cases these variations can be represented by bifurcation diagram that shows how the attractor landscape changes in relation to a single control parameter (Kelso and Engstrom 2006, 124-137). Most human behaviors, however, require that multiple parameters are taken into account. Now, provided that the important variables and parameters for describing characteristic variations of a certain behavior for an individual can be determined (a very difficult task, in most cases), one could, in theory, construct a comprehensive “habit topology” for that behavior: a map of how that behavior’s preferred states change in relation to various parameters. Notice that, depending on the parameters involved, some stabilities of this habit topology will be visited by the system more or less regularly. For instance, in the case of quadruped motion, assuming that the parameter of speed varies regularly over its natural range, a quadruped (e.g. horse) regularly visits the various gaits (walk, trot, gallop) that make up the preferred states of its habit topology (Schöner and Kelso, 1988, 1516; Hoyt and Taylor, 1981). However, for some behaviors, especially those that are sensitive to multiple parameters, certain regions of the habit topology can remain “hidden” because the required values of the relevant control parameters are rarely if ever encountered. Imagine, for example, that a person who never dances might be found, on one occasion, happily dancing the night away. Conventionally speaking, this behavior is not habitual. But from a dynamic view, it is hard to say. Perhaps on that occasion the person encountered just the right combination of circumstances—excellent mood, pleasurable company, Afro-Cuban music, fantastic mojitos, etc.—that made, for that person, dancing a very deep (and enjoyable) stability. If these circumstances will regularly facilitate the same behavior for that person, cannot we say that dancing is habitual for them in those circumstances? The point here is not to insist on this characterization, but to question our conventional understanding of habits, which typically involves assumptions about “normal” circumstances. Are habitual behaviors only rightfully considered as such if we regularly encounter the circumstances that facilitate their expression? If not, how would we determine the unexpressed or latent habits of a person, independently of circumstances? Third, it is important to consider that the attractor landscape of a particular behavior commonly has multiple stabilities even within restricted parameter values (Schöner and Kelso 1988, 1518). This phenomenon of multistability implies that “habitual behavior” may not be always the same even when all relevant variables are the same. In such cases, which stability describes the habit? The stability into which the system enters may depend on its recent history or on a symmetry breaking. For example, as represented by the much-studied HKB model (Chemero 2009), coordinated finger movement—waving the two index fingers in time with a metronome, where tempo or speed is the main control parameter—exhibits bistability at slower speeds and monostability at faster speeds (Kelso 1995). Within the slower, bistable regime, which of the two stable states the system exhibits may depend on its historical trajectory: for instance, if the system has just entered the bistable regime from the monostable regime, it will remain in the preferred state of the latter. Although coordinated finger movement may not seem representative of human behavior, coordination dynamics and its telltale characteristics—such as multistability—have been found in a wide range of behavioral and neural systems (Schöner and Kelso 1988; Kelso 2012), suggesting an important implication: perhaps what a person presently exhibits as habitual behavior within certain circumstances does not uniquely characterize what is habitual for that person even within those circumstances, but must also be understood as a result of a particular historical trajectory. The importance of history is also indicated by the phenomenon of hysteresis (Haken 2003, 8-9), i.e., when the state or behavior of a system is influenced by the residual stability of an antecedent regime. Thus certain behaviors might persist even after the attractor landscape has changed so that they are no longer “habitual” within the current context.Finally, if we define learning in terms of alterations to the attractor landscape for a particular behavior such that some states are newly stabilized while others are destabilized (Kostrubiec et al. 2012), the interrelatedness of habits as implied by the previous three points indicates that habits are rarely altered in a piecemeal fashion: learning affects entire clusters of habits that are composed of shared components. That is, learning affects an entire “habit space,” and not just individual habits in isolation (Kelso 1995, 159-186). This further complicates the picture of personal habits, as well as the kinds of learning strategies we should adopt to change them. For instance, it suggests that certain habitual behaviors that are difficult to target can be altered indirectly by focusing on other, related behaviors. It also suggests that in many cases—especially where a complex task demands a finely articulated set of behaviors—training should focus on shaping the overall “habit space” rather than each individual behavior. Moreover, as implied by the definition of learning just given, the dynamical approach suggests that habits are a necessary condition for learning and not just a product—contrary to the so-called “blank slate” model (Kostrubiec et al. 2012). In conclusion, we see that a fairly simple definition of habit in terms of dynamic stability yields a number of insights that question our conventional notion of personal habits as slow-changing, context-independent, uniquely repetitive, and discrete behaviors. At the same time, a dynamical view can give an account of the relative fixity of behaviors that we take to be habitual in the conventional sense. However, by showing that this fixity is dynamically and relationally constituted, a dynamical view reveals the elaborate context in which all habits are embedded. Moreover, human habits appear to be instances of a very general pattern: all living systems exhibit self-organized stabilities that reduce their degrees of freedom, producing robust but flexible repertoires of behavior. (shrink)

This work addresses a broad range of questions which belong to four fields: computation theory, general philosophy of science, philosophy of cognitive science, and philosophy of mind. Dynamical system theory provides the framework for a unified treatment of these questions. ;The main goal of this dissertation is to propose a new view of the aims and methods of cognitive science--the dynamical approach . According to this view, the object of cognitive science is a particular set of dynamical systems, which (...) I call "cognitive systems". The goal of a cognitive study is to specify a dynamical model of a cognitive system, and then use this model to produce a detailed account of the specific cognitive abilities of that system. The dynamical approach does not limit a-priori the form of the dynamical models which cognitive science may consider. In particular, this approach is compatible with both computational and connectionist modeling, for both computational systems and connectionist networks are special types of dynamical systems. ;To substantiate these methodological claims about cognitive science, I deal first with two questions in two different fields: What is a computational system? What is a dynamical explanation of a deterministic process? ;Intuitively, a computational system is a deterministic system which evolves in discrete time steps, and which can be described in an effective way. In chapter 1, I give a formal definition of this concept which employs the notions of isomorphism between dynamical systems, and of Turing computable function. In chapter 2, I propose a more comprehensive analysis which is based on a natural generalization of the concept of Turing machine. ;The goal of chapter 3 is to develop a theory of the dynamical explanation of a deterministic process. By a "dynamical explanation" I mean the specification of a dynamical model of the system or process which we want to explain. I start from the analysis of a specific type of explanandum--dynamical phenomena--and I then use this analysis to shed light on the general form of a dynamical explanation. Finally, I analyze the structure of those theories which generate explanations of this form, namely dynamical theories. (shrink)

We explore the dynamical behavior of two f(T, B) gravity models with a scalar field: 1. $$f(T,B)=T-\gamma log\bigg [\frac{\psi B_{0}}{B}\bigg ]$$ and 2. $$f(T,B)=\eta T+\frac{\zeta }{B^{n}}$$, using the potential $$V(\phi )=V_{0}(\alpha +e^{-\beta \phi })^{-\delta }$$ and an interaction term $$\bar{Q} = \epsilon H \dot{\phi }^2$$. A phase space analysis reveals four fixed points in Model 3.1 (three stable, one saddle) and five in Model 3.2 (four stable), indicating transitions from matter to dark energy dominance. With interaction, Model 3.2 exhibits seven (...) fixed points, including five stable, one unstable (stiff matter era) and one saddle point. Evolution of the deceleration parameter q and the total EoS parameter $$\omega _{tot}$$ confirms sustained cosmic acceleration, with present values $$q_{0} = -1.005$$ and $$\omega _{0} = -0.556$$ (Model 3.1) and $$q_{0} = -1.245$$ and $$\omega _{0}=-1.0404$$ (Model 3.2). Comparisons of our observationally constrained parameters with $$\Lambda$$ CDM show strong consistency, supporting the viability of these models in describing the late-time accelerated expansion of the Universe. (shrink)

Current models of speech motor control rely on either trajectory-based control (DIVA, GEPPETO, ACT) or a dynamical systems approach based on feedback control (Task Dynamics, FACTS). While both approaches have provided insights into the speech motor system, it is difficult to connect these findings across models given the distinct theoretical and computational bases of the two approaches. We propose a new extension of the most widely used dynamical systems approach, Task Dynamics, that incorporates many of the strengths (...) of trajectory-based approaches, providing a way to bridge the theoretical divide between what have been two separate approaches to understanding speech motor control. The Task Dynamics (TD) model posits that speech gestures are governed by point attractor dynamics consistent with a critically damped harmonic oscillator. Kinematic trajectories associated with such gestures should therefore be consistent with a second-order dynamical system, possibly modified by blending with temporally overlapping gestures or altering oscillator parameters. This account of observed kinematics is powerful and theoretically appealing, but may be insufficient to account for deviations from predicted kinematics—i.e., changes produced in response to some external perturbations to the jaw, changes in control during acquisition and development, or effects of word/syllable frequency. Optimization, such as would be needed to minimize articulatory effort, is also incompatible with the current TD model, though the idea that the speech production systems economizes effort has a long history and, importantly, also plays a critical role in current theories of domain-general human motor control. To address these issues, we use Dynamic Movement Primitives (DMPs) to expand a dynamical systems framework for speech motor control to allow modification of kinematic trajectories by incorporating a simple, learnable forcing term into existing point attractor dynamics. We show that integration of DMPs with task-based point-attractor dynamics enhances the potential explanatory power of TD in a number of critical ways, including the ability to account for external forces in planning and optimizing both kinematic and dynamic movement costs. At the same time, this approach preserves the successes of Task Dynamics in handling multi-gesture planning and coordination. (shrink)

The paper presents a logical treatment of actions based on dynamic logic. This approach makes it possible to reflect clearly the differences between static and dynamic elements of the world, a distinction which seems crucial to us for a representation of actions.Starting from propositional dynamic logic a formal system (DLA) is developed, the programs of which are used to model action types. Some special features of this system are: Basic aspects of time are incorporated in DLA as far (...) as they are needed for our purpose. Names for states and for instants are simulated by formulas. It is possible to express formally that a formula is satisfiable or valid. A special program is introduced to reflect developments which are not caused by an official agent but by external influences. (shrink)

ABSTRACT Against empiricist and rationalist prejudices concerning the nature of issues related to “mental health,” this article offers a phenomenological account of identity as developed in a meaningful system with the environment or world. Drawing on the work of Merleau-Ponty and Dewey, I argue that behavioral and emotional health and illness must be understood in terms of the plasticity or rigidity, respectively, of the individual's responses in the face of new and threatening environmental demands. However, individual plasticity and rigidity (...) are not given qualities of the individual but are themselves developed in healthy or unhealthy interpersonal environments. I discuss three cases of emotional and behavioral trouble in order to explore the manner in which unhealthy self-environment systems can undermine individuals' powers of adaptability and growth. (shrink)

In this paper we present a dynamic assignment language which extends the dynamic predicate logic of Groenendijk and Stokhof [1991: 39–100] with assignment and with generalized quantifiers. The use of this dynamic assignment language for natural language analysis, along the lines of o.c. and [Barwise, 1987: 1–29], is demonstrated by examples. We show that our representation language permits us to treat a wide variety of donkey sentences: conditionals with a donkey pronoun in their consequent and quantified sentences with donkey pronouns (...) anywhere in the scope of the quantifier. It is also demonstrated that our account does not suffer from the so-called proportion problem.Discussions about the correctness or incorrectness of proposals for dynamic interpretation of language have been hampered in the past by the difficulty of seeing through the ramifications of the dynamic semantic clauses (phrased in terms of input-output behaviour) in non-trivial cases. To remedy this, we supplement the dynamic semantics of our representation language with an axiom system in the style of Hoare. While the representation languages of barwise and Groenendijk and Stokhof were not axiomatized, the rules we propose form a deduction system for the dynamic assignment language which is proved correct and complete with respect to the semantics. (shrink)