Imagery and meaning,the cognitive science connection

Taking the integrated viewpoints of causal theory of reference, cognitive science and the notion of correspondence principles from physics, this paper addresses the problems of creativity, the nature of visual imagery and the manner in which science progresses.     

Bayes,predictive processing,and the cognitive architecture of motor control

Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical; they posit generative models at multiple distinct “levels,” whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising levels of generative models. I argue that this view is not entailed by a general Bayesian/predictive processing outlook. Bayesian approaches are compatible with distinct formats of mental representation. Focusing on Bayesian approaches to motor control, I argue that the junctures between different types of mental representation are places where the transitivity of hierarchical prediction may be broken, and I consider the upshot of this conclusion for broader discussions of cognitive architecture.     

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.     

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.     

A Bayesian marriage of science and politics

Conclusion Some might say that there is a sense in which the very consideration of whether science is equated with rationality is obscene. For far too long science has been dealt with by philosophers within the confines of a protectionist, if not an apologist, policy. Putnam has provided a service by exposing some of the weaker links of the scientism mythology. I have tried to bolster that critique by indicating how, along Bayesian lines, value and holistic considerations could be used to help positively transform science.Richard Rudner would have undoubtedly agreed with very little of what I have said — he seldon did. But he would have been there with open-mind and open-heart. Forqua mentor andqua friend he was, indeed, the philosopher par excellence.     

Mind,consciousness, and cognition: Phenomenology vs. cognitive science

I would like to thank Steven Crowell from Rice University (Philosophy Department) for helpful comments and suggestions about my discussion of Husserl and other phenomenologists, and Edouard Philippe, also from Rice University (Electrical Engineering Department), for offering me the opportunity to formulate my views on cognitive science and artificial intelligence.     

Causes of cultural disparity: Switches,tuners, and the cognitive science of religion

Cultural disparity – the variation across cultural traits such as knowledge, skill, and belief – is a complex phenomenon, studied by a number of researchers with an expanding empirical toolkit. While there is a growing consensus as to the processes that generate cultural variation and change, general explanatory frameworks require additional tools for identifying, organizing, and relating the complex causes that underpin the production of cultural disparity. Here I develop a case study in the cognitive science of religion and demonstrate how concepts and distinctions drawn from work on contrastive explanation and manipulationist accounts of causation provide such tools for distinguishing explanatory levels, organizing causal narratives, and accounting for cross-cultural patterns.     

A computational cognitive framework of spatial memory in brains and robots

Computational cognitive models of spatial memory often neglect difficulties posed by the real world, such as sensory noise, uncertainty, and high spatial complexity. On the other hand, robotics is unconcerned with understanding biological cognition. Here, we describe a computational framework for robotic architectures aiming to function in realistic environments, as well as to be cognitively plausible.We motivate and describe several mechanisms towards achieving this despite the sensory noise and spatial complexity inherent in the physical world. We tackle error accumulation during path integration by means of Bayesian localization, and loop closing with sequential gradient descent. Finally, we outline a method for structuring spatial representations using metric learning and clustering. Crucially, unlike the algorithms of traditional robotics, we show that these mechanisms can be implemented in neuronal or cognitive models.We briefly outline a concrete implementation of the proposed framework as part of the LIDA cognitive architecture, and argue that this kind of probabilistic framework is well-suited for use in cognitive robotic architectures aiming to combine spatial functionality and psychological plausibility.     

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.