Theoretical status of computational cognitive modeling

This article explores the view that computational models of cognition may constitute valid theories of cognition, often in the full sense of the term “theory”. In this discussion, this article examines various (existent or possible) positions on this issue and argues in favor of the view above. It also connects this issue with a number of other relevant issues, such as the general relationship between theory and data, the validation of models, and the practical benefits of computational modeling. All the discussions point to the position that computational cognitive models can be true theories of cognition.     

Multidisciplinarity and cognitive science

The aim of Schunn, Crowley and Okada's (1998) study is to address the question of whether the current state of cognitive science, as represented by Cognitive Science and the Cognitive Science Society, “reflects the multidisciplinary ideals of its foundation.” To properly interpret and respond to their results, we need to ask a prior question: What is cognitive science's multidisciplinary ideal? There are at least two conceptions—a “localist” conception, which seems to be implicit in Schunn, Crowley and Okada's discussion, and a “holist” conception. I argue that while both have been endorsed by some cognitive scientists, there are reasons for preferring the holist conception. I then consider what Schunn, Crowley and Okada's findings tell us about the state of cognitive science in light of a holist approach and report on an analysis of the journal's contents which looks at the domain, subdomain, and cognitive capacity investigated.     

Representation and cognitive science

‘Representation’ is a concept which occurs both in cognitive science and philosophy. It has common features in both settings in that it concerns the explanation of behaviour in terms of the way the subject categorizes and systematizes responses to its environment. The prevailing model sees representations as causally structured entities correlated on the one hand with elements in a natural language and on the other with clearly identifiable items in the world. This leads to an analysis of representation and cognition in terms of formal symbols and their relations. But human perception and cognition use multiple informational constraints and deal with unsystematic and messy input in a way best explained by Parallel Distributed Processing models. This undermines the claim that a formal representational theory of mind is ‘the only game in town’. In particular it suggests a radically different model of brain function and its relation to epistemology from that found in current representational theories.     

Tolerant enactivist cognitive science

Enactivist (Embodied, Embedded, etc.) approaches in cognitive science and philosophy of mind are sometimes, though not always, conjoined with an anti-representational commitment. A weaker anti-representational claim is that ascribing representational content to internal/sub-personal processes is not compulsory when giving psychological explanations. A stronger anti-representational claim is that the very idea of ascribing representational content to internal, sub-personal processes is a theoretical confusion. This paper criticises some of the arguments made by Hutto and Myin (2013, 2017) for the stronger anti-representational claim and suggests that the default Enactivist view should be the weaker non-representational position.     

Innateness in cognitive science

Innateness is one of the central concepts of cognitive science; but it is also a source of considerable confusion. In this article, I survey recent attempts to understand the notion of innateness as it figures in cognitive science and indicate which is likely to prove most fruitful. One approach draws directly on our "commonsense" views about innate traits. Another aims to characterize innateness in terms of concepts drawn from biology, such as genetic determination. Yet neither strategy has met with much success. This could indicate that a satisfactory account of innateness needs to make use of the conceptual resources of cognitive science itself. A proposal that takes this suggestion seriously is outlined, and an appeal is made for a more systematic assessment of the role and significance of the notion of innateness to cognitive science.     

Semantics and the computational paradigm in cognitive psychology

There is a prevalent notion among cognitive scientists and philosophers of mind that computers are merely formal symbol manipulators, performing the actions they do solely on the basis of the syntactic properties of the symbols they manipulate. This view of computers has allowed some philosophers to divorce semantics from computational explanations. Semantic content, then, becomes something one adds to computational explanations to get psychological explanations. Other philosophers, such as Stephen Stich, have taken a stronger view, advocating doing away with semantics entirely. This paper argues that a correct account of computation requires us to attribute content to computational processes in order to explain which functions are being computed. This entails that computational psychology must countenance mental representations. Since anti-semantic positions are incompatible with computational psychology thus construed, they ought to be rejected. Lastly, I argue that in an important sense, computers are not formal symbol manipulators.     

A computational cognitive model of syntactic priming

The psycholinguistic literature has identified two syntactic adaptation effects in language production: rapidly decaying short-term priming and long-lasting adaptation. To explain both effects, we present an ACT-R model of syntactic priming based on a wide-coverage, lexicalized syntactic theory that explains priming as facilitation of lexical access. In this model, two well-established ACT-R mechanisms, base-level learning and spreading activation, account for long-term adaptation and short-term priming, respectively. Our model simulates incremental language production and in a series of modeling studies, we show that it accounts for (a) the inverse frequency interaction; (b) the absence of a decay in long-term priming; and (c) the cumulativity of long-term adaptation. The model also explains the lexical boost effect and the fact that it only applies to short-term priming. We also present corpus data that verify a prediction of the model, that is, that the lexical boost affects all lexical material, rather than just heads.     

Introduction to the special issue on computational cognitive modeling

This special issue of Cognitive Systems Research features the top twelve papers from the 4^th International Conference on Cognitive Modeling (ICCM-2001). These papers represent the current trends in computational cognitive modeling, displaying both the diversity and commonalities of the field. This introduction to the special issue describes the motivations for the conference and the special issue, and overviews the diversity and commonalities found in the papers.     

Explanatory pluralism in cognitive science

This brief commentary has three goals. The first is to argue that "framework debate" in cognitive science is unresolvable. The idea that one theory or framework can singly account for the vast complexity and variety of cognitive processes seems unlikely if not impossible. The second goal is a consequence of this: We should consider how the various theories on offer work together in diverse contexts of investigation. A final goal is to supply a brief review for readers who are compelled by these points to explore existing literature on the topic. Despite this literature, pluralism has garnered very little attention from broader cognitive science. We end by briefly considering what it might mean for theoretical cognitive science.     

Non-representationalist cognitive science and realism

Embodied and extended cognition is a relatively new paradigm within cognitive science that challenges the basic tenet of classical cognitive science, viz. cognition consists in building and manipulating internal representations. Some of the pioneers of embodied cognitive science have claimed that this new way of conceptualizing cognition puts pressure on epistemological and ontological realism. In this paper I will argue that such anti-realist conclusions do not follow from the basic assumptions of radical embodied cognitive science. Furthermore I will show that one can develop a form of realism that reflects rather than just accommodates the core principles of non-representationalist embodied cognitive science.     

Twelve issues for cognitive science

I am struck by how little is known about so much of cognition. One goal of this paper is to argue for the need to consider a rich set of interlocking issues in the study of cognition. Mainstream work in cognition—including my own—ignores many critical aspects of animate cognitive systems. Perhaps one reason that existing theories say so little relevant to real world activities is the neglect of social and cultural factors, of emotion, and of the major points that distinguish an animate cognitive system from an artificial one: the need to survive, to regulate its own operation, to maintain itself, to exist in the environment, to change from a small, uneducated, immature system to an adult, developed, knowledgeable one. Human cognition is not the same as artificial cognition, if only because the human organism must also be concerned with the problems of life, of development, of survival. There must be a regulatory system that interacts with the cognitive component. And it may well be that it is the cognitive component that is subservient, evolved primarily for the benefit of the regulatory system, working through the emotions, through affect. I argue that several concepts must become fundamental parts of the study of cognition, including the roles of culture, of social interaction, of emotions, and of motivation. I argue that there are at least 12 issues that should comprise the study of cognition, and thereby, the field of Cognitive Science. We need to study a wide variety of behavior before we can hope to understand a single class. Cognitive scientists as a whole ought to make more use of evidence from the neurosciences, from brain damage and mental illness, from cognitive sociology and anthropology, and from clinical studies of the human. These must be accompanied, of course, with the study of language, of the psychological aspects of human processing structures, and of artificially intelligent mechanisms. The study of Cognitive Science requires a complex interaction among different issues of concern, an interaction that will not be properly understood until all parts are understood, with no part independent of the others, the whole requiring the parts, and the parts the whole.     

Dynamical approaches to cognitive science

Dynamical ideas are beginning to have a major impact on cognitive science, from foundational debates to daily practice. In this article, I review three contrasting examples of work in this area that address the lexical and grammatical structure of language, Piaget's classic 'A-not-B' error, and active categorical perception in an embodied, situated agent. From these three examples, I then attempt to articulate the major differences between dynamical approaches and more traditional symbolic and connectionist approaches. Although the three models reviewed here vary considerably in their details, they share a focus on the unfolding trajectory of a system's state and the internal and external forces that shape this trajectory, rather than the representational content of its constituent states or the underlying physical mechanisms that instantiate the dynamics. In some work, this dynamical viewpoint is augmented with a situated and embodied perspective on cognition, forming a promising unified theoretical framework for cognitive science broadly construed.