Representations in dynamical embodied agents: re-analyzing a minimally cognitive model agent

Understanding the role of 'representations' in cognitive science is a fundamental problem facing the emerging framework of embodied, situated, dynamical cognition. To make progress, I follow the approach proposed by an influential representational skeptic, Randall Beer: building artificial agents capable of minimally cognitive behaviors and assessing whether their internal states can be considered to involve representations. Hence, I operationalize the concept of representing as 'standing in,' and I look for representations in embodied agents involved in simple categorization tasks. In a first experiment, no representation can be found, but the relevance of the task is undermined by the fact that agents with no internal states can reach high performance. A simple modification makes the task more "representationally hungry," and in this case, agents' internal states are found to qualify as representations. I conclude by discussing the benefits of reconciling the embodied-dynamical approach with the notion of representation.     

Extending the classical view of representation

Representation has always been a central part of models in cognitive science, but this idea has come under attack. Researchers advocating the alternative approaches of perceptual symbol systems, situated action, embodied cognition, and dynamical systems have argued against central assumptions of the classical representational approach to mind. We review the core assumptions of the representational view and these four suggested alternatives. We argue that representation should remain a core part of cognitive science, but that the insights from these alternative approaches must be incorporated into models of cognitive processing.     

Discussions Dynamical Explanation in Cognitive Science

Summary  Applying the concepts of dynamical systems theory to explain cognitive phenomena is still a fairly recent trend in cognitive science and its potential and consequences are not nearly mapped out. A decade ago, dynamical approaches were introduced as a paradigm shift in cognitive science and in this paper I concentrate on how to substantiate this claim. After having considered and rejected the possibility that continuous time is the crucial factor, I present Kelso’s model of a near-cognitive phenomenon which invokes self-organization as the guiding principle. Then, the explanatory strategy implicit in this approach is explicated and its underlying assumption presented. Finally, I discuss how we should characterize this explanatory framework using the notion of emergence.     

Emergence and reduction in dynamical cognitive science

This paper examines the widespread intuition that the dynamical approach to cognitive science is importantly related to emergentism about the mind. The explanatory practices adopted by dynamical cognitive science rule out some conceptions of emergence; covering law explanations require a deducibility relationship between explanans and explanandum, whereas canonical theories of emergence require the absence of such deducibility. A response to this problem - one which would save the intuition that dynamics and emergence are related - is to reconstrue the concept of emergence as a relationship between laws. I call this “nomological emergence” and comment on the extent to which dynamicists would find it acceptable. Alternatively, dynamical cognitive science might be viewed as fitting better with the kind of “functional reductionism” which has recently been developed by authors such as Jaegwon Kim. Which of these two alternatives is preferable remains an open question pending the further development of dynamical cognitive science, particularly in its “non-classical” forms.     

The extended body: a case study in the neurophenomenology of social interaction

There is a growing realization in cognitive science that a theory of embodied intersubjectivity is needed to better account for social cognition. We highlight some challenges that must be addressed by attempts to interpret ‘simulation theory’ in terms of embodiment, and argue for an alternative approach that integrates phenomenology and dynamical systems theory in a mutually informing manner. Instead of ‘simulation’ we put forward the concept of the ‘extended body’, an enactive and phenomenological notion that emphasizes the socially mediated nature of embodiment. To illustrate the explanatory potential of this approach, we replicate an agent-based model of embodied social interaction. An analysis of the model demonstrates that the extended body can be explained in terms of mutual dynamical entanglement: inter-bodily resonance between individuals can give rise to self-sustaining interaction patterns that go beyond the behavioral capacities of isolated individuals by modulating their intra-bodily conditions of behavior generation.     

Evolutionary Psychology, Cognitive Science, and Dynamical Systems: Building an Integrative Paradigm

Cognitive science, evolutionary psychology, and dynamical systems theory have all been proposed as frameworks for linking the diverse subdisciplines of psychology with one another, and with other scientific disciplines. Traditional cognitive science focused on content-free general processing and deemphasized motivation. An evolutionary perspective emphasizes the centrality of motivational systems and the specificity of mechanisms designed to solve particular recurrent problems. The evolutionary perspective provides a set of broad general principles linking diverse behaviors in humans as well as other species. The dynamic approach seeks even broader principles, searching for emergent patterns in all complex systems, whether animate or inanimate. Natural selection is itself one such broad principle, as is the broader principle of self-organization, which helps explain dynamic equilibria found in groups of humans and in diverse species linked together within ecosystems. Proponents of the major contending interdisciplines will need to build more bridges if the dream of a unifying paradigm is to be realized. This review samples some of the reasons why evolutionary psychologists, dynamical systems theorists, and traditional cognitive scientists need one another.     

Artificial life: organization, adaptation and complexity from the bottom up

Artificial life attempts to understand the essential general properties of living systems by synthesizing life-like behavior in software, hardware and biochemicals. As many of the essential abstract properties of living systems (e.g. autonomous adaptive and intelligent behavior) are also studied by cognitive science, artificial life and cognitive science have an essential overlap. This review highlights the state of the art in artificial life with respect to dynamical hierarchies, molecular self-organization, evolutionary robotics, the evolution of complexity and language, and other practical applications. It also speculates about future connections between artificial life and cognitive science.     

Rethinking the explanatory power of dynamical models in cognitive science

In this paper I offer an interventionist perspective on the explanatory structure and explanatory power of (some) 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.     

Representations and Cognitive Explanations: Assessing the Dynamicist's Challenge in Cognitive Science

Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that they are mistaken. Nonetheless, DST does offer new ideas as to the format of representations employed in cognitive systems. With respect to explanation, I argue that some DST models are better seen as conforming to the covering-law conception of explanation than to the mechanistic conception of explanation implicit in most cognitive science research. But even here, I argue, DST models are a valuable complement to more mechanistic cognitive explanations.     

Experimental design: Problems in understanding the dynamical behavior-environment system

In this paper, I attempt to describe the implications of dynamical approaches to science for research in the experimental study of behavior. I discuss the differences between classical and dynamical science, and focus on how dynamical science might see replication differently from classical science. Focusing on replication specifically, I present some problems that the classical approach has in dealing with dynamics and multiple causation. I ask about the status and meaning of "error" variance, and whether it may be a potent source of information. I show how a dynamical approach can handle the sort of control by past events that is hard for classical science to understand. These concerns require, I believe, an approach to variability that is quite different from the one most researchers currently employ. I suggest that some of these problems can be overcome by a notion of "behavioral state," which is a distillation of an organism's history.     

Theories and Theorizers: A Contextual Approach to Theories of Cognition

An undisputable characteristic of cognitive science is its enormous diversity of theories. Not surprisingly, these often belong to different paradigms that focus on different processes and levels of analysis. A related problem is that researchers of cognition frequently seem to ascribe to incompatible approaches to research, creating a Tower of Babel of cognitive knowledge. This text presents a pragmatic model of meta-theoretical analysis, a theory conceived of to examine other theories, which allows cognitive theories to be described, integrated and compared. After a brief introduction to meta-theoretical analysis in cognitive science, the dynamic and structural components of a theory are described. The analysis of conceptual mappings between components and explanation strategies is also described, as well as the processes of intra-theory generalization and inter-theory comparison. The various components of the meta-theoretical model are presented with examples of different cognitive theories, mainly focusing on two current approaches to research: The dynamical approach to cognition and the computer metaphor of mind. Finally, two potential counter arguments to the model are presented and discussed.     

What Is the Model of Trust for Multi-agent Systems? Whether or Not E-Trust Applies to Autonomous Agents

A socio-cognitive approach to trust can help us envisage a notion of networked trust for multi-agent systems (MAS) based on different interacting agents. In this framework, the issue is to evaluate whether or not a socio-cognitive analysis of trust can apply to the interactions between human and autonomous agents. Two main arguments support two alternative hypothesis; one suggests that only reliance applies to artificial agents, because predictability of agents’ digital interaction is viewed as an absolute value and human relation is judged to be a necessary requirement for trust. The other suggests that trust may apply to autonomous agents because predictability of agents’ interaction is viewed only as a relative value since the digital normativity that grows out of the communication process between interacting agents in MAS has always deal with some unpredictable outcomes (reduction of uncertainty). Furthermore, human touch is not judged to be a necessary requirement for trust. In this perspective, a diverse notion of trust is elaborated, as trust is no longer conceived only as a relation between interacting agents but, rather, as a relation between cognitive states of control and lack of control (double bind).     

PERSONS AND THE EXTENDED-MIND THESIS

The extended-mind thesis (EM) is the claim that mentality need not be situated just in the brain, or even within the boundaries of the skin. Some versions take "extended selves" be to relatively transitory couplings of biological organisms and external resources. First, I show how EM can be seen as an extension of traditional views of mind. Then, after voicing a couple of qualms about EM, I reject EM in favor of a more modest hypothesis that recognizes enduring subjects of experience and agents with integrated bodies. Nonetheless, my modest hypothesis allows subpersonal states to have nonbiological parts that play essential roles in cognitive processing. I present empirical warrant for this modest hypothesis and show how it leaves room for science and religion to coexist.     

Appraisal of certain methodologies in cognitive science based on Lakatos’s methodology of scientific research programmes

Attempts to apply the mathematical tools of dynamical systems theory to cognition in a systematic way has been well under way since the early 90s and has been recognised as a “third contender” to computationalist and connectionist approaches (Eliasmith in Philos Psychol 9(4):441–463, 1996). Nevertheless, it was also realised that such an application will not lead to a solid paradigm as straightforwardly as was initially hoped (Eliasmith 1996; van Leeuwen in Minds Mach 15:271–333, 2005). In this paper I explicate a method for assessing such proposals by drawing upon Lakatos’s (in: Lakatos, Musgrave (eds) Criticism and the growth of knowledge, Cambridge University Press, London, pp 91–195, 1970) methodology of scientific research programs (hereafter: “MSRP”). MSRP focuses on the heuristics of a particular field and gauges the model/theory building stratagems by reference to theoretical and empirical progress, on the one hand, and the continuity and the autonomy of the way the field’s heuristic generates its series of models/theories, on the other. The requirement of continuity and autonomy afford distinct senses of ad hoc-ness, which serve as an effective tool to detect various subtleties which may otherwise be missed: the present approach identifies shortcomings missed by Chemero’s (Radical embodied cognitive science, The MIT Press, Cambridge, 2009) radical embodied cognitive science and falsifies Chemero’s claim that the methodological powers of his model-based account is on a par with computationalism. In general, I claim that MSRP is relevant to current methodological issues in cognitive science and can supplement debates regarding “local” assessments of methodologies, such as that between mechanical versus covering-law explanations. MSRP must at least be viewed as a necessary constraint for any methodological considerations in cognitive science.

     

The methodological role of mechanistic-computational models in cognitive science

This paper discusses the relevance of models for cognitive science that integrate mechanistic and computational aspects. Its main hypothesis is that a model of a cognitive system is satisfactory and explanatory to the extent that it bridges phenomena at multiple mechanistic levels, such that at least several of these mechanistic levels are shown to implement computational processes. The relevant parts of the computation must be mapped onto distinguishable entities and activities of the mechanism. The ideal is contrasted with two other accounts of modeling in cognitive science. The first has been presented by David Marr in combination with a distinction of “levels of computation”. The second builds on a hierarchy of “mechanistic levels” in the sense of Carl Craver. It is argued that neither of the two accounts secures satisfactory explanations of cognitive systems. The mechanistic-computational ideal can be thought of as resulting from a fusion of Marr’s and Craver’s ideals. It is defended as adequate and plausible in light of scientific practice, and certain metaphysical background assumptions are discussed.

     

Religion is natural,atheism is not: On why everybody is both right and wrong

After discussing evidence of irreligion and the rise of the so called “New Atheism”, the authors refute the claim that this poses a problem for the cognitive science of religion and its hypothesis that religion is natural. The “naturalness hypothesis” is not deterministic but probabilistic and thus leaves room for atheism. This, the authors maintain, is true of both the by‐product and adaptationist stances within the cognitive science of religion. In this context the authors also discuss the memetic or “unnaturalness” hypothesis, i.e. that religion is a “virus of the mind”. The authors criticize accounts of atheism offered by cognitive scientists of religion as being based on unfounded assumptions about the psychology of atheists, and object to the notion that the natural aspects of religion by corollary make atheism unnatural. By considering human cognition in a semiotic framework and emphasizing its natural ability to take part in semiotic systems of signs, atheism emerges as a natural, cognitive strategy. The authors argue that to reach a fuller account of religion, the cognitive (naturalness) and memetic (unnaturalness) hypotheses of religion must be merged. Finally, a preliminary analysis of the “New Atheism” is offered in terms of semiotic and cognitive dynamics     

Adding Deleuze to the mix

In this article I will suggest ways in which adding the French philosopher Gilles Deleuze to the mix can complement and extend the 4EA approach to cognitive science. In the first part of the paper, I will show how the Deleuzean tripartite ontological difference (virtual/intensive/actual) can provide an explicit ontology for dynamical systems theory. The second part will take these ontological notions and apply them to three areas of concern to the 4EA approaches: (a) the Deleuzean concept of the virtual will clarify the ontological status of perceptual capacity as sensorimotor skill; (b) the Deleuzean concept of “intensive individuation” will clarify the ontological status of the genesis of perceptually guided behavior; (c) the Deleuzean critique of confusing the actual and the virtual will enable us to intervene in the realism/idealism debate. These aspects will not be addressed sequentially but will be interwoven into an unfolding argument.     

Connectionism and the Philosophical Foundations of Cognitive Science

This is an overview of recent philosophical discussion about connectionism and the foundations of cognitive science. Connectionist modeling in cognitive science is described. Three broad conceptions of the mind are characterized, and their comparative strengths and weaknesses are discussed: (1) the classical computation conception in cognitive science; (2) a popular foundational interpretation of connectionism that John Tienson and I call "non-sentential computationalism"; and (3) an alternative interpretation of connectionism we call "dynamical cognition." Also discussed are two recent philosophical attempts to enlist connectionism in defense of eliminativism about folk psychology.     

Radical embodiment: neural dynamics and consciousness

We propose a new approach to the neuroscience of consciousness, growing out of the ‘enactive’ viewpoint in cognitive science. This approach aims to map the neural substrates of consciousness at the level of large-scale, emergent and transient dynamical patterns of brain activity (rather than at the level of particular circuits or classes of neurons), and it suggests that the processes crucial for consciousness cut across the brain–body–world divisions, rather than being brain-bound neural events. Whereas standard approaches to the neural correlates of consciousness have assumed a one-way causal-explanatory relationship between internal neural representational systems and the contents of consciousness, our approach allows for theories and hypotheses about the two-way or reciprocal relationship between embodied conscious states and local neuronal activity.