In a matter of mere milliseconds, conversational partners can transform their expectations about the world in a way that accords with another person's perspective. At the same time, in similar situations, the exact opposite also appears to be true. Rather than being at odds, these findings suggest that there are multiple contextual and processing constraints that may guide when and how people consider perspective. These constraints are shaped by a host of factors, including the availability of social and environmental (...) cues, and intrinsic biases and cognitive abilities. To explain how these might be integrated in a new way forward, we turn to an adaptive account of interpersonal interaction. This account draws from basic principles of dynamical systems, principles that we argue are already expressed, both implicitly and explicitly, within a broad landscape of existing research. We then showcase an initial attempt to develop a computational framework to instantiate some of these principles. This framework, consisting of what we argue to be important mechanistic insights rendered by neural network models, is based on a promising and long-standing approach that has yet to take hold in the current domain. We argue that by bridging this gap, new insights into other theoretical accounts, such as the connections between memory and common ground information, might be revealed. (shrink)

ABSTRACTIn this paper I offer an interventionist perspective on the explanatory structure and explanatory power of dynamical models in cognitive science: I argue that some “pure” dynamical models – ones that do not refer to mechanisms at all – in cognitive science are “contextualized causal models” and that this explanatory structure gives such models genuine explanatory power. I contrast this view with several other perspectives on the explanatory power of “pure” dynamical models. One of the main results is that dynamical (...) models need not refer to underlying mechanisms in order to be explanatory. I defend and illustrate this position in terms of dynamical models of the A-not-B error in developmental psychology as elaborated by Thelen and colleagues, and dynamical models of unintentional interpersonal coordination developed by Richardson and colleagues. (shrink)

Vector models of language are based on the contextual aspects of language, the distributions of words and how they co-occur in text. Truth conditional models focus on the logical aspects of language, compositional properties of words and how they compose to form sentences. In the truth conditional approach, the denotation of a sentence determines its truth conditions, which can be taken to be a truth value, a set of possible worlds, a context change potential, or similar. In the vector (...) models, the degree of co-occurrence of words in context determines how similar the meanings of words are. In this paper, we put these two models together and develop a vector semantics for language based on the simply typed lambda calculus models of natural language. We provide two types of vector semantics: a static one that uses techniques familiar from the truth conditional tradition and a dynamic one based on a form of dynamic interpretation inspired by Heim’s context change potentials. We show how the dynamic model can be applied to entailment between a corpus and a sentence and provide examples. (shrink)

Ethics involves an organized, reasoned approach to gathering and processing data in order to arrive at decisions about what to do, what to value, and/or what virtues to cultivate. A model is proposed for conceptualizing this complex dynamic, which incorporates elements of both rule-and-principle ethics and the ethic of care. The model suggested here has two levels. The first level identifies the components that comprise philosophical reasoning; the second contextualizes and operationalizes the model in relation to (...) the processor’s philosophical stance on the nature of knowing. Three philosophical stances are identified and described: science-dominant, person-dominant, and science-person equilibrium. Physicians tend to process patients from first perspectives, nurses from second. Hence, health team collaboration in moral problem solving is critically important. (shrink)

This aim of this paper is two-fold: it critically analyses and rejects accounts blending active inference as theory of mind and enactivism; and it advances an enactivist-dynamic understanding of social cognition that is compatible with active inference. While some social cognition theories seemingly take an enactive perspective on social cognition, they explain it as the attribution of mental states to other people, by assuming representational structures, in line with the classic Theory of Mind. Holding both enactivism and ToM, we (...) argue, entails contradiction and confusion due to two ToM assumptions widely known to be rejected by enactivism: that social cognition reduces to mental representation and social cognition is a hardwired contentful ‘toolkit’ or ‘starter pack’ that fuels the model-like theorising supposed in. The paper offers a positive alternative, one that avoids contradictions or confusion. After rejecting ToM-inspired theories of social cognition and clarifying the profile of social cognition under enactivism, that is without assumptions and, the last section advances an enactivist-dynamic model of cognition as dynamic, real-time, fluid, contextual social action, where we use the formalisms of dynamical systems theory to explain the origins of socio-cognitive novelty in developmental change and active inference as a tool to demonstrate social understanding as generalised synchronisation. (shrink)

Coherence and correspondence are classical contenders as theories of truth. In this paper we examine them instead as interacting factors in the dynamics of belief across epistemic networks. We construct an agent-based model of network contact in which agents are characterized not in terms of single beliefs but in terms of internal belief suites. Individuals update elements of their belief suites on input from other agents in order both to maximize internal belief coherence and to incorporate ‘trickled in’ elements (...) of truth as correspondence. Results, though often intuitive, prove more complex than in simpler models (Hegselmann & Krause 2002, 2006; Grim, Singer, Reade & Fisher 2015). The optimistic finding is that pressures toward internal coherence can exploit and expand on small elements of truth as correspondence is introduced into epistemic networks. Less optimistic results show that pressures for coherence can also work directly against the incorporation of truth, particularly when coherence is established first and new data is introduced later. (shrink)

This book examines the legal principle of judicial independence in comparative perspective with the goal of advancing a better understanding of the idea of an independent judiciary more generally. From an initial survey of judicial systems in different countries, it is clear that the understanding and practice of judicial independence take a variety of forms. Scholarly literature likewise provides a range of views on what judicial independence means, with scholars often advocating a preferred conception of a model court for (...) achieving 'true judicial independence' as part of a rule of law system. This book seeks to reorient the prevailing approach to the study of judicial independence by better understanding how judicial independence operates within domestic legal systems in its institutional and legal dimensions. It asks how and why different conceptualisations of judicial independence emerge over time by comparing detailed case studies of courts in two legally pluralistic states, which share inheritances of British rule and the common law. By tracing the development of judicial independence in the legal systems of Malaysia and Pakistan from the time of independence to the present, the book offers an insightful comparison of how judicial independence took shape and developed in these countries over time. From this comparison, it suggests a number of contextual factors that can be seen to play a role in the evolution of judicial independence. The study draws upon the significant divergence observed in the case studies to propose a refined understanding of the idea of an independent judiciary, termed the 'pragmatic and context-sensitive theory', which may be seen in contradistinction to a universal approach. While judicial independence responds to the core need of judges to be perceived as an impartial third party by constructing formal and informal constraints on the judge and relationships between judges and others, its meaning in a legal system is inevitably shaped by the judicial role along with other features at the domestic level. The book concludes that the adaptive and pragmatic qualities of judicial independence supply it with relevance and legitimacy within a domestic legal system. (shrink)

Realist interpretations of quantum mechanics presuppose the existence of elements of reality that are independent of the actions used to reveal them. Such a view is challenged by several no-go theorems that show quantum correlations cannot be explained by non-contextual ontological models, where physical properties are assumed to exist prior to and independently of the act of measurement. However, all such contextuality proofs assume a traditional notion of causal structure, where causal influence flows from past to future according to (...) ordinary dynamical laws. This leaves open the question of whether the apparent contextuality of quantum mechanics is simply the signature of some exotic causal structure, where the future might affect the past or distant systems might get correlated due to non-local constraints. Here we show that quantum predictions require a deeper form of contextuality: even allowing for arbitrary causal structure, no model can explain quantum correlations from non-contextual ontological properties of the world, be they initial states, dynamical laws, or global constraints. (shrink)

The overall goal of this target article is to demonstrate a mechanism for an embodied cognition. The particular vehicle is a much-studied, but still widely debated phenomenon seen in 7–12 month-old-infants. In Piaget's classic “A-not-B error,” infants who have successfully uncovered a toy at location “A” continue to reach to that location even after they watch the toy hidden in a nearby location “B.” Here, we question the traditional explanations of the error as an indicator of infants' concepts of objects (...) or other static mental structures. Instead, we demonstrate that the A-not-B error and its previously puzzling contextual variations can be understood by the coupled dynamics of the ordinary processes of goal-directed actions: looking, planning, reaching, and remembering. We offer a formal dynamic theory and model based on cognitive embodiment that both simulates the known A-not-B effects and offers novel predictions that match new experimental results. The demonstration supports an embodied view by casting the mental events involved in perception, planning, deciding, and remembering in the same analogic dynamic language as that used to describe bodily movement, so that they may be continuously meshed. We maintain that this mesh is a pre-eminently cognitive act of “knowing” not only in infancy but also in everyday activities throughout the life span. Key Words: cognitive development; dynamical systems theory; embodied cognition; infant development; motor control; motor planning; perception and action. (shrink)

Cognition is context-sensitive, as the same sensory information is processed differently depending on its context (e.g., on its probabilistic association with goal-directed actions and their outcomes). Despite this, the concept of context in studies of higher-order cognitive processes, like cognitive control, is often simplified to nominal stimulus categories (like a target vs. distractor). Here we propose that quantifying contextual information to model cognitive demands is (1) fruitful as it can provide novel insight into the nature of cognitive control, (...) (2) accessible as simple probability models offer a tool for quantifying context and (3) analytically useful as a fine-grained quantification of context can be entered into more complex models as regressors that allow a direct way of appropriately exploring many of the defining tenants of cognitive control (e.g., rapidly changing trial-by-trial neural dynamics). Here, we briefly describe the logic of using context-sensitive measures of cognitive control and highlight recent studies from this approach using simple information theory metrics. (shrink)

This article addresses salient conceptual issues in social organisational psychology in probing change in organisational systems, e.g., culture, innovation and implementation, reflective practice and change models. Insights from chaos–complexity research in the natural sciences which underpin the dynamics of flux and change to unravel the hidden, the unexplained, the disordered will be built on to explore the phenomena of change from a social psychological perspective. The concept of nano-psychology is introduced to open up a creative debate in the social psychological (...) field on creative change which builds on the nano-insights evolving in the natural science field. (shrink)

Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modelling probabilistic-dynamic systems using two aspects of quantum theory. The first, 'contextuality', is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, 'quantum (...) entanglement', allows cognitive phenomena to be modeled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light. Introducing the basic principles in an easy-to-follow way, this book does not assume a physics background or a quantum brain and comes complete with a tutorial and fully worked-out applications in important areas of cognition and decision. (shrink)

We propose the SIMS model can be strengthened by detailing the dynamic interaction between sensorimotor activation and contextual conceptual information. Rapidly activated evaluations and contextual knowledge can guide and constrain embodied simulations. In addition, we stress the potential importance of extending the SIMS model to dynamic social interactions that go beyond the passive observer.

Following an article by John von Neumann on infinite tensor products, we develop the idea that the usual formalism of quantum mechanics, associated with unitary equivalence of representations, stops working when countable infinities of particles (or degrees of freedom) are encountered. This is because the dimension of the corresponding Hilbert space becomes uncountably infinite, leading to the loss of unitary equivalence, and to sectorisation. By interpreting physically this mathematical fact, we show that it provides a natural way to describe the (...) “Heisenberg cut”, as well as a unified mathematical model including both quantum and classical physics, appearing as required incommensurable facets in the description of nature. (shrink)

We presented a contextual statistical model of the probabilistic description of physical reality. Here contexts (complexes of physical conditions) are considered as basic elements of reality. There is discussed the relation with QM. We propose a realistic analogue of Bohr’s principle of complementarity. In the opposite to the Bohr’s principle, our principle has no direct relation with mutual exclusivity for observables. To distinguish our principle from the Bohr’s principle and to give better characterization, we change the terminology and (...) speak about supplementarity, instead of complementarity. Supplementarity is based on the interference of probabilities. It has quantitative expression trough a coefficient which can be easily calculated from experimental statistical data. We need not appeal to the Hilbert space formalism and noncommutativity of operators representing observables. Moreover, in our model there exists pairs of supplementary observables which cannot be represented in the complex Hilbert space. There are discussed applications of the principle of supplementarity outside quantum physics. (shrink)

While Specific Informed Consent has been the established standard for obtaining consent for medical research for many years, it does not appear suitable for large-scale biobank and health data research. Thus, alternative forms of consent have been suggested, based on a variety of ethical background assumptions. This article identifies five main ethical perspectives at stake. Even though Tiered Consent, Dynamic Consent and Meta Consent are designed to the demands of the self-determination perspective as well as the perspective of research (...) as a public good, they are still also criticized from both perspectives. In addition, criticisms based on concerns of justice, participation and democratic deliberation, and relational concerns have been levelled at each of the models. As all of these perspectives have valid points to make, the task at hand lies in balancing these ethical perspectives. What constitutes an adequate balancing depends on contextual factors. These factors include digital infrastructure and digital literacy, data safety regulation, good scientific and clinical practice, transparent debates on ethically relevant features of research, social inequalities, anti-discrimination laws and practices, trust in health care institutions and recognition of patient preferences, and consensus on unethical research. We argue that the role of context in determining acceptable models of consent puts the ethical importance of models of consent into perspective. Since altering contextual factors can help to live up to the ethical concerns at stake in debates about models of consent, opting for such a shift of focus comes without ethical loss. (shrink)

Within natural language semantics, pronouns are often thought to correspond to variables whose values are contributed by contextual assignment functions. This paper concerns the application of this idea to cases where the antecedent of a pronoun is a plural quantifiers. The paper discusses the modelling of accessibility patterns of quantifier antecedents in a dynamic theory of interpretation. The goal is to reach a semantics of quantificational dependency which yields a fully semantic notion of pronominal accessibility. I argue that (...) certain dependency phenomena that arise in quantificationally created contexts require a representation of context wherein the labelling of antecedents is not rigid but rather dynamic itself. I propose a stack-based alternative to classic assignment functions, along the lines of Vermeulen (1993) and van Eijck (2001), and give a dynamic semantics of quantification which correctly accommodates the problematic anaphoric phenomena. (shrink)

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-trial modeling to unravel perceptual learning processes and their neurophysiological counterparts. (shrink)

Applying causal methods to fields such as healthcare, marketing, and economics receives increasing interest. In particular, optimising the individual-treatment-effect – often referred to as uplift modelling – has peaked in areas such as precision medicine and targeted advertising. While existing techniques have proven useful in many settings, they suffer vividly in a dynamic environment. To address this issue, we propose a novel optimisation target that is easily incorporated in bandit algorithms. Incorporating this target creates a causal model which (...) we name an uplifted contextual multi-armed bandit. Experiments on real and simulated data show the proposed method to effectively improve upon the state-of-the-art. All our code is made available online at https://github.com/vub-dl/u-cmab. (shrink)

Abstract While agreeing that dynamical models play a major role in cognitive science, we reject Stepp, Chemero, and Turvey's contention that they constitute an alternative to mechanistic explanations. We review several problems dynamical models face as putative explanations when they are not grounded in mechanisms. Further, we argue that the opposition of dynamical models and mechanisms is a false one and that those dynamical models that characterize the operations of mechanisms overcome these problems. By briefly considering examples involving the generation (...) of action potentials and circadian rhythms, we show how decomposing a mechanism and modeling its dynamics are complementary endeavors. (shrink)

ArgumentWe continue our analysis of modeling practices that focus more on qualitative understanding of system behavior than the attempt to provide sharp forecasts. The argument here is built around three episodes: the ambitious work of the Princeton Meteorological Project; the seemingly simple models of convection in weather systems by Edward Lorenz at MIT; and then finally analysis of the dripping faucet by Robert Shaw and the Dynamical Systems Collective at UC Santa Cruz. Using the Princeton Meteorological Project as an argumentative (...) foil for the later chaos work of Lorenz and Shaw, we first show how the epistemological interest of modeling came to shift fromissuingpredictions toprobingthe very meaning and limits of prediction. The second step of our argument shows that what may be seen in one context of use as a modeling technology that is error ridden, imprecise, or inadequate, may be parsed completely differently in another context. This argument about technology and practice, we argue, feeds through to epistemological conceptions of error. Far from being something that can be defined in the absolute, the notion of error is shown to be contextually plastic. (shrink)

By leveraging the case of Hindu sati, this paper elucidates the ways in which structure and culture condition suicidal behavior by way of social psychological and emotional dynamics. Conventionally, sati falls under Durkheim's discussion of altruistic suicides, or the self-sacrifice of underindividuated or excessively integrated peoples like widows in traditional societies. In light of the fact that Durkheim's interpretation was based on uneven data, nineteenth century Eurocentric beliefs, and a theoretical framework that can no longer resist modification and elaboration, by (...) reconsidering sati it is possible to sketch a new model that strengthens Durkheim's theory by making it more robust and generalizable. The following model is built on five principles. First, integration and regulation are not distinct causal forces, but overlapping contextual conditions. Second, to better explain the variation in suicidality across time and space, we must also pay attention to culture as it provides the underlying meanings of suicide that can increase the odds a person or class of persons become suicidal or are protected against suicidality. Third, structure still matters, but in many cases, the role power and power-differentials play must be considered. Fourth, understanding why and how people choose suicide depends on incorporating identity and status processes. Fifth, because the expression of social emotions like shame are patterned by structural and cultural conditions, to understand how suicidality is socioculturally patterned we must further explore the link between identity/status, social emotions, and structure and culture. (shrink)

The semantically ambiguous nature of the sign and aspects of non-classicality of elementary matter as described by quantum theory show remarkable coherent analogy. We focus on how the ambiguous nature of the image, text and art work bears functional resemblance to the dynamics of contextuality, entanglement, superposition, collapse and decoherence as these phenomena are known in quantum theory. These quantumlike properties in linguistic signs have previously been identified in formal descritions of e.g. concept combinations and mental lexicon representations and have (...) been reported on in the literature. In this approach the informationalized, communicated, mediatized conceptual configuration—of e.g. the art work—in the personal reflected mind behaves like a quantum state function in a higher dimensional complex space, in which it is time and again contextually collapsed and further cognitively entangled. The observer–consumer of signs becomes the empowered ‘produmer’ creating the cognitive outcome of the interaction, while loosing most of any ‘classical givenness’ of the sign. These quantum-like descriptions are now developed here in four example aesthetic signs; the installation Mist room by Ann Veronica Janssens, the installation Sections of a happy moment by David Claerbout, the photograph The Falling Man by Richard Drew and the documentary Huicholes. The Last Peyote Guardians by Vilchez and Stefani. Our present work develops further the use of a previously developed quantum model for concept representation in natural language. In our present approach of the aesthetic sign, we extend to individual—idiosyncratic—observer contexts instead of socially shared group contexts, and as such also include multiple idiosyncratic creation of meaning and experience. This irreducible superposition emerges as the core feature of the aesthetic sign and is most critically embedded in the ‘no-interpretation’ interpretation of the documentary signal. (shrink)

Academic research suggests that variances in contextual dynamics, and more specifically religion, may lead to disparate perceptions and practices of corporate social responsibility. Driven by the increased geopolitical and economic importance of the Middle East and identified gaps in knowledge, the study aims to examine if indeed there is a divergent form of CSR exercised in the region. The study identifies unique CSR dimensions and constructs presented through an empirical framework in order to outline the practice and perception of (...) CSR in a context with strong Islamic beliefs. The framework goes beyond the platform of mere Islamic philanthropy and is based on CSR-stakeholder management practices. Following an exploratory research design and collecting interview data from representatives of 63 organisations from Saudi Arabia, the United Arab Emirates and Oman, the study offers a snapshot of the CSR reality from the perspective of those living the phenomenon. The results suggest that the practice and perception of CSR in the examined context are largely grounded in the areas of social and altruistic actions but they cannot be examined in isolation from the religious context of CSR operation. This focus is mainly attributed to the dominant role of Islam in the examined sample, which leads to forms of non-structured or semi-structured approaches to CSR. Apart from the theoretical advancements offered to the CSR literature, the study also provides contributions for practitioners and policy makers. (shrink)

Francois Recanati presents the basic features of the *indexical model* of mental files, and defends it against several interrelated objections. According to this model, mental files refer to objects in a way that is analogous to that of indexicals in language: a file refers to an object in virtue of a contextual relation between them. For instance, perception and attention provide the basis for demonstrative files. Several objections, some of them from David Papineau, concern the possibility of (...) files to preserve and add information about objects across contexts. How is it possible to think about the same object when the subject no longer is in the original context? How is it possible to think of a perceived object as already known? Can this be done without an explicit identity judgment? Recanati answers these questions by invoking mental files of non-basic kinds and by describing the cognitive dynamics in which they take part. (shrink)

The vigorous development of online education has produced massive amounts of education data. How to mine and analyze education big data has become an urgent problem in the field of education and big data knowledge engineering. As for the dynamic learning data, knowledge tracing aims to track learners’ knowledge status over time by analyzing the learners’ exercise data, so as to predict their performance in the next time step. Deep learning knowledge tracking performs well, but they mainly model (...) the knowledge components while ignoring the personalized information of questions and learners, and provide limited interpretability in the interaction between learners’ knowledge status and questions. A context-aware attentive knowledge query network model is proposed in this paper, which combines flexible neural network models with interpretable model components inspired by psychometric theory. We use the Rasch model to regularize the embedding of questions and learners’ interaction tuples, and obtain personalized representations from them. In addition, the long-term short-term memory network and monotonic attention mechanism are used to mine the contextual information of learner interaction sequences and question sequences. It can not only retain the ability to model sequences, but also use the monotonic attention mechanism with exponential decay term to extract the hidden forgetting behavior and other characteristics of learners in the learning process. Finally, the vector dot product is used to simulate the interaction between the learners’ knowledge state and questions to improve the interpretability. A series of experimental results on 4 real-world online learning datasets show that CAKQN has the best performance, and its AUC value is improved by an average of 2.945% compared with the existing optimal model. Furthermore, the CAKQN proposed in this paper can not only track learners’ knowledge status like other models but also model learners’ forgetting behavior. In the future, our research will have high application value in the realization of personalized learning strategies, teaching interventions, and resource recommendations for intelligent online education platforms. (shrink)

Kaplan and Craver claim that all explanations in neuroscience appeal to mechanisms. They extend this view to the use of mathematical models in neuroscience and propose a constraint such models must meet in order to be explanatory. I analyze a mathematical model used to provide explanations in dynamical systems neuroscience and indicate how this explanation cannot be accommodated by the mechanist framework. I argue that this explanation is well characterized by Batterman’s account of minimal model explanations and that (...) it demonstrates how relationships between explanatory models in neuroscience and the systems they represent is more complex than has been appreciated. (shrink)

Abstract: I argue that for psychological and social reasons, the traditional “Conflict Model” of science and religion interactions has such a strong hold on the nonexpert imagination that counterexamples and claims that interactions are simply more complex than the model allows are inadequate to undermine its power. Taxonomies, such as those of Ian Barbour and John Haught, which characterize conflict as only one among several possible relationships, help. But these taxonomies, by themselves, fail to offer an account of (...) why different relationships prevail among different communities and how they succeed one another within particular communities—that is, they contain no dynamic elements. To undermine the power of the “Conflict Model,” we should be seeking to offer alternative models for science and religion interactions that can both incorporate the range of stances articulated by scholars like Barbour and which can offer an account of the process by which differing attitudes succeed one another. As a step toward this goal, I propose a general “interacting subcultures model” and illustrate its applicability in a small number of mini-case studies from Early Modern Britain and France and with glances toward contemporary America. (shrink)

The debate over the explanatory nature of cognitive models has been waged mostly between two factions: the mechanists and the dynamical systems theorists. The former hold that cognitive models are explanatory only if they satisfy a set of mapping criteria, particularly the 3M/3m* requirement. The latter have argued, pace the mechanists, that some cognitive models are both dynamical and constitute covering-law explanations. In this paper, I provide a minimal model interpretation of dynamical cognitive models, arguing that this both provides (...) needed clarity to the mechanist versus dynamicist divide in cognitive science and also paves the way towards further insights about scientific explanation generally. (shrink)

Ten new graduate speech pathologists recounted their experiences in managing workplace ethical dilemmas in semi-structured interviews. Their stories were analysed for elements that described the nature and management of the ethical dilemmas. Ethical reasoning themes were generated to reflect the participants’ approaches to managing these dilemmas. Finally, a conceptual model, the Dynamic Model of Ethical Reasoning, was developed. This model incorporates the elements of awareness, independent problem solving, supported problem solving, and decision and outcome evaluation. Features (...) of the model demonstrate the complexity of ethical reasoning and the challenges that new graduates encounter when managing ethical dilemmas. The results have implications for preparing new graduates to manage ethical dilemmas in the workplace. (shrink)

What is the viewpoint regarding the emotional lives of sages in the Zhuangzi 莊子? There are two conflicting positions in current scholarship: sages have emotions, and sages are without emotions. In this essay, we introduce these positions with their corresponding textual support and show that they are not satisfactory accounts. Specifically, we point out that the conflict arises as scholars adopt a static model of emotions. Thus, we propose that a better way to understand the emotional lives of sages (...) is to adopt a dynamic model of emotions characterized by the process of forgetting. Through the discussion of such a dynamic process, we show how conflicting textual evidence can be integrated into this dynamic process and, at the same time, be read consistently. Ultimately, we argue that the ideal emotional lives of sages in the Zhuangzi adopt a dynamic model of emotions characterized by the vacillation of activity of the mind between the state with and without emotions. (shrink)

Van Gelder has presented a position which he ties closely to a broad class of models known as dynamical models. While supporting many of his broader claims about the importance of this class (as has been argued by connectionists for quite some time), I note that there are a number of unique characteristics of his brand of dynamicism. I suggest that these characteristics engender difficulties for his view.

This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected on April 27, 1999.

Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representations of a system.

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

In the real world, individual resources are crucial for patients when epidemics outbreak. Thus, the coupled dynamics of resource diffusion and epidemic spreading have been widely investigated when the recovery of diseases significantly depends on the resources from neighbors in static social networks. However, the social relationships of individuals are time-varying, which affects such coupled dynamics. For that, we propose a coupled resource-epidemic dynamic model on a time-varying multiplex network to synchronously simulate the resource diffusion and epidemic spreading (...) in dynamic social networks. The equilibrium analysis of the coupled model is conducted in a general scenario where the resource generation varies between susceptible and infected states and the recovery rate changes between resourceful and noresource states. By using the microscopic Markov chain approach and Monte Carlo simulations, we determine a probabilistic framework of the intralayer and interlayer dynamic processes of the coupled model and obtain the outbreak threshold of epidemic spreading. Meanwhile, the experimental results show the trivially asymmetric interactions between resource diffusion and epidemic spreading. They also indicate that the stronger activity heterogeneity and the larger contact capacity of individuals in the resource layer can more greatly promote resource diffusion, effectively suppressing epidemic spreading. However, these two individual characters in the epidemic layer can cause more resource depletion, which greatly promotes epidemic spreading. Furthermore, we also find that the contact capacity finitely impacts the coupled dynamics of resource diffusion and epidemic spreading. (shrink)

Individuals make decisions under uncertainty every day based on incomplete information concerning the potential outcome of the choice or chance levels. The choices individuals make 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 two-choice task with variable risk between sure loss and risky loss to illustrate how a simple nonlinear dynamical system can be employed to capture the dynamics (...) of human decision-making under uncertainty (i.e., multi-stability, 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 using dynamical models for explaining the nonlinear complexities of human decision-making are discussed, as well as the degree to which nonlinear dynamical systems theory might offer an alternative framework for understanding human decision-making processes. (shrink)

While there is an extensive literature on the tendency to mimic emotional expressions in adults, it is unclear how this skill emerges and develops over time. Specifically, it is unclear whether infants mimic discrete emotion-related facial actions, whether their facial displays are moderated by contextual cues and whether infants’ emotional mimicry is constrained by developmental changes in the ability to discriminate emotions. We therefore investigate these questions using Baby-FACS to code infants’ facial displays and eye-movement tracking to examine infants’ (...) looking times at facial expressions. Three-, 7-, and 12-month-old participants were exposed to dynamic facial expressions of a virtual model which either looked at the infant or had an averted gaze. Infants did not match emotion-specific facial actions shown by the model, but they produced valence-congruent facial responses to the distinct expressions. Furthermore, only the 7- and 12-month-olds displayed negative responses to the model’s negative expressions and they looked more at areas of the face recruiting facial actions involved in specific expressions. Our results suggest that valence-congruent expressions emerge in infancy during a period where the decoding of facial expressions becomes increasingly sensitive to the social signal value of emotions. (shrink)

We present a dynamic programming model which is used to investigate hypothermia as an adaptive response by small passerine birds in winter. The model predicts that there is a threshold function of reserves during the night, below which it is optimal to enter hypothermia, and above which it is optimal to rest. This threshold function decreases during the night, with a particularly sharp drop at the end of the night, representing the time and energy costs associated with (...) returning to normal body temperature. The results of the model emphasise the trade-off between energy and predation, not just between foraging options, but also between foraging during the day and entering hypothermia at night. The value of being able to use hypothermia represents not just energy savings, but also reduced predation risk due to changes in the optimal foraging strategy. Conditions which give a high value of hypothermia are short photoperiod, variable food supply, low temperatures, poor and scarce food supplies. (shrink)

The theory of imperatives is philosophically relevant since in building it — some of the long standing problems need to be addressed, and presumably some new ones are waiting to be discovered. The relevance of the theory of imperatives for philosophical research is remarkable, but usually recognized only within the field of practical philosophy. Nevertheless, the emphasis can be put on problems of theoretical philosophy. Proper understanding of imperatives is likely to raise doubts about some of our deeply entrenched and (...) tacit presumptions. In philosophy of language it is the presumption that declaratives provide the paradigm for sentence form; in philosophy of science it is the belief that theory construction is independent from the language practice, in logic it is the conviction that logical meaning relations are constituted out of logical terminology, in ontology it is the view that language use is free from ontological commitments. The list is not exhaustive; it includes only those presumptions that this paper concerns. (shrink)

Opinion leaders are informal leaders who have the ability to influence others' decisions about adopting new products, practices or ideas. In the healthcare setting, the importance of translating new research evidence into practice has led to interest in understanding how opinion leaders could be used to speed this process. Despite continued interest, gaps in understanding opinion leadership remain. Agent‐based models are computer models that have proven to be useful for representing dynamic and contextual phenomena such as opinion leadership. (...) The purpose of this paper is to describe the work conducted in preparation for the development of an agent‐based model of nursing opinion leadership. The aim of this phase of the model development project was to clarify basic assumptions about opinions, the individual attributes of opinion leaders and characteristics of the context in which they are effective. The process used to clarify these assumptions was the construction of a preliminary nursing opinion leader model, derived from philosophical theories about belief formation. (shrink)