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)

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)

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)

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)

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)

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.

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 (...) class='Hi'>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)

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.

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)

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 balance between births and deaths in an age-structured population is strongly influenced by the spatial distribution of sub-populations. Our aim was to describe the demographic process of a fish population in an hierarchical dendritic river network, by taking into account the possible movements of individuals. We tried also to quantify the effect of river network changes (damming or channelling) on the global fish population dynamics. The Salmo trutta life pattern was taken as an example for.We proposed a model which (...) includes the demographic and the migration processes, considering migration fast compared to demography. The population was divided into three age-classes and subdivided into fifteen spatial patches, thus having 45 state variables. Both processes were described by means of constant transfer coefficients, so we were dealing with a linear system of difference equations. The discrete case of the variable aggregation method allowed the study of the system through the dominant elements of a much simpler linear system with only three global variables: the total number of individuals in each age-class. (shrink)

Describing actions entails that relations between objects are discovered. A pervasively neural account of this process requires that fundamental problems are solved: the neural pointer problem, the binding problem, and the problem of generating discrete processing steps from time-continuous neural processes. We present a prototypical solution to these problems in a neural dynamic model that comprises dynamic neural fields holding representations close to sensorimotor surfaces as well as dynamic neural nodes holding discrete, language-like representations. Making the connection between these two (...) types of representations enables the model to describe actions as well as to perceptually ground movement phrases—all based on real visual input. We demonstrate how the dynamic neural processes autonomously generate the processing steps required to describe or ground object-oriented actions. By solving the fundamental problems of neural pointing, binding, and emergent discrete processing, the model may be a first but critical step toward a systematic neural processing account of higher cognition. (shrink)

Reciprocity is a decisive behavioural rule resulting in successful co-operation or deterrence. In this paper, a dynamic model is proposed, where reciprocity is described by changes in altruistic (or malevolent) ties. Multiple steady states may exist in one of which there may be general cooperation (solidarity) and the other being one of universal malice (war of each individual against all other individuals). We apply our theory to a number of examples, illustrating that the agents’ initial preferences determine whether a steady (...) state of solidarity, selfishness or malice will emerge. (shrink)

Experts in Artificial Intelligence (AI) development predict that advances in the development of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance is not made prudently and critically-reflexively, it can result in negative outcomes for humanity. For this reason, several researchers in the area are trying to develop a robust, beneficial, and safe concept of AI for the preservation of humanity and the environment. Currently, several of the open problems in the field of (...) AI research arise from the difficulty of avoiding unwanted behaviors of intelligent agents and systems, and at the same time specifying what we want such systems to do, especially when we look for the possibility of intelligent agents acting in several domains over the long term. It is of utmost importance that artificial intelligent agents have their values aligned with human values, given the fact that we cannot expect an AI to develop human moral values simply because of its intelligence, as discussed in the Orthogonality Thesis. Perhaps this difficulty comes from the way we are addressing the problem of expressing objectives, values, and ends, using representational cognitive methods. A solution to this problem would be the dynamic approach proposed by Dreyfus, whose phenomenological philosophy shows that the human experience of being-in-the-world in several aspects is not well represented by the symbolic or connectionist cognitive method, especially in regards to the question of learning values. A possible approach to this problem would be to use theoretical models such as SED (situated embodied dynamics) to address the values learning problem in AI. (shrink)

How does the human brain link relational concepts to perceptual experience? For example, a speaker may say “the cup to the left of the computer” to direct the listener's attention to one of two cups on a desk. We provide a neural dynamic account for both perceptual grounding, in which relational concepts enable the attentional selection of objects in the visual array, and for the generation of descriptions of the visual array using relational concepts. In the model, activation in neural (...) populations evolves dynamically under the influence of both inputs and strong interaction as formalized in dynamic field theory. Relational concepts are modeled as patterns of connectivity to perceptual representations. These generalize across the visual array through active coordinate transforms that center the representation of target objects in potential reference objects. How the model perceptually grounds or generates relational descriptions is probed in 104 simulations that systematically vary the spatial and movement relations employed, the number of feature dimensions used, and the number of matching and nonmatching objects. We explain how sequences of decisions emerge from the time‐ and state‐continuous neural dynamics, how relational hypotheses are generated and either accepted or rejected, followed by the selection of new objects or the generation of new relational hypotheses. Its neural realism distinguishes the model from information processing accounts, its capacity to autonomously generate sequences of processing steps distinguishes it from deep neural network accounts. The model points toward a neural dynamic theory of higher cognition. (shrink)

A gravitational model is proposed that relates the terrestrially measured value of the gravitational constantG directly to the density and angular velocity of the galaxy. The model indicates a constant scalar value forG within most regions of our galaxy, but predicts thatG will be different in other galaxies and zero in intergalactic space. The model offers explanations for galactic cluster stability, discrepancies in terrestrial measurements ofG, and atomic particle stability. The model also provides a causal relationship between strong, electromagnetic, weak, (...) and gravitational interactions. The two postulates required for the proposed model reduce to two assumptions made in GRT in regions whereG is constant; these postulates are consistent with the existence of a 2.7 K blackbody background radiation. (shrink)

Inferences from clinical research results to estimates of therapeutic effectiveness suffer due to various biases. I argue that predictions of medical effectiveness are prone to failure because current medical research overlooks the impacts of a particularly detrimental set of biases: meta-biases. Meta-biases are linked to higher-level characteristics of medical research and their effects are only observed when comparing sets of studies that share certain meta-level properties. I offer a model for correcting research results based on meta-research evidence, the bias dynamics (...) model, which employs regularly updated empirical bias coefficients to attenuate estimates of therapeutic effectiveness. (shrink)

This paper presents a dynamic perspective in which the psychological contract is treated as a structured set of beliefs that are held by individual employees about the mutual obligations of the organization as employer and themselves as employees. This set of beliefs is assumed to produce a state of commitment to the organization in which the employee is willing to accept work roles and tasks offered by the organization, and to carry them out in accordance with certain standards. The dynamic (...) model that is presented can help to explain why the commitment of employees remains relatively stable over time, and why it may suddenly decrease or increase under circumstances that are perceived as critical by the employee. The model assumes that the employee's evaluation of the organization's behavior changes over time, but that the structure of the psychological contract and the associated commitment change only when certain limits are overstepped. This perspective on changes in the psychological contract transforms the concept into a powerful construct that may lead to fruitful research on the dynamics of organization-employee relationships. Implications for future research are discussed. (shrink)

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)

We present a neural dynamic model that perceptually grounds nested noun phrases, that is, noun phrases that contain further (possibly also nested) noun phrases as parts. The model receives input from the visual array and a representation of a noun phrase from language processing. It organizes a search for the denoted object in the visual scene. The model is a neural dynamic architecture of interacting neural populations which has clear interfaces with perceptual processes. It solves a set of theoretical challenges, (...) including the problem of keeping a nested structure in short-term memory in a way that solves the problem of 2 and massive binding problem emphasized by Jackendoff. The model organizes a search for the objects that are referenced in that structure. We motivate the model, demonstrate simulation results, and discuss how it differs from related models. (shrink)

We present a neural dynamic model that perceptually grounds nested noun phrases, that is, noun phrases that contain further (possibly also nested) noun phrases as parts. The model receives input from the visual array and a representation of a noun phrase from language processing. It organizes a search for the denoted object in the visual scene. The model is a neural dynamic architecture of interacting neural populations which has clear interfaces with perceptual processes. It solves a set of theoretical challenges, (...) including the problem of keeping a nested structure in short-term memory in a way that solves the problem of 2 and massive binding problem emphasized by Jackendoff. The model organizes a search for the objects that are referenced in that structure. We motivate the model, demonstrate simulation results, and discuss how it differs from related models. (shrink)