Selection procedures for module discovery : exploring evolutionary algorithms for cognitive science

Evolutionary algorithms are playing an increasingly important role as search methods in cognitive science domains. In this study, methodological issues in the use of evolutionary algorithms were investigated via simulations in which procedures were systematically varied to modify the selection pressures on populations of evolving agents. Traditional roulette wheel, tournament, and variations of these selection algorithms were compared on the “needle-in-a-haystack” problem developed by Hinton and Nowlan in their 1987 study of the Baldwin effect. The task is an important one for cognitive science, as it demonstrates the power of learning as a local search technique in smoothing a fitness landscape that lacks gradient information. One aspect that has continued to foster interest in the problem is the observation of residual learning ability in simulated populations even after long periods of time. Effective evolutionary algorithms balance their search effort between broad exploration of the search space and in-depth exploitation of promising solutions already found. Issues discussed include the differential effects of rank and proportional selection, the tradeoff between migration of populations towards good solutions and maintenance of diversity, and the development of measures that illustrate how each selection algorithm affects the search process over generations. We show that both roulette wheel and tournament algorithms can be modified to appropriately balance search between exploration and exploitation, and effectively eliminate residual learning in this problem.

Cognitive neuroimaging: Cognitive science out of the armchair

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.

Religion Explained? : A Philosophical Appraisal of the Cognitive Science of Religion

This study examines philosophically the main theories and methodological assumptions of the field known as the cognitive science of religion (CSR). The study makes a philosophically informed reconstruction of the methodological principles of the CSR, indicates problems with them, and examines possible solutions to these problems. The study focuses on several different CSR writers, namely, Scott Atran, Justin Barrett, Pascal Boyer and Dan Sperber. CSR theorising is done in the intersection between cognitive sciences, anthropology and evolutionary psychology. This multidisciplinary nature makes CSR a fertile ground for philosophical considerations coming from philosophy of psychology, philosophy of mind and philosophy of science. The study begins by spelling out the methodological assumptions and auxiliary theories of CSR writers by situating these theories and assumptions in the nexus of existing approaches to religion. The distinctive feature of CSR is its emphasis on information processing: CSR writers claim that contemporary cognitive sciences can inform anthropological theorising about the human mind and offer tools for producing causal explanations. Further, they claim to explain the prevalence and persistence of religion by cognitive systems that undergird religious thinking. I also examine the core theoretical contributions of the field focusing mainly on the (1) “minimally counter-intuitiveness hypothesis” and (2) the different ways in which supernatural agent representations activate our cognitive systems. Generally speaking, CSR writers argue for the naturalness of religion: religious ideas and practices are widespread and pervasive because human cognition operates in such a way that religious ideas are easy to acquire and transmit. The study raises two philosophical problems, namely, the “problem of scope” and the “problem of religious relevance”. The problem of scope is created by the insistence of several critics of the CSR that CSR explanations are mostly irrelevant for explaining religion. Most CSR writers themselves hold that cognitive explanations can answer most of our questions about religion. I argue that the problem of scope is created by differences in explanation-begging questions: the former group is interested in explaining different things than the latter group. I propose that we should not stick too rigidly to one set of methodological assumptions, but rather acknowledge that different assumptions might help us to answer different questions about religion. Instead of adhering to some robust metaphysics as some strongly naturalistic writers argue, we should adopt a pragmatic and explanatory pluralist approach which would allow different kinds of methodological presuppositions in the study of religion provided that they attempt to answer different kinds of why-questions, since religion appears to be a multi-faceted phenomenon that spans over a variety of fields of special sciences. The problem of religious relevance is created by the insistence of some writers that CSR theories show religious beliefs to be false or irrational, whereas others invoke CSR theories to defend certain religious ideas. The problem is interesting because it reveals the more general philosophical assumptions of those who make such interpretations. CSR theories can (and have been) interpreted in terms of three different philosophical frameworks: strict naturalism, broad naturalism and theism. I argue that CSR theories can be interpreted inside all three frameworks without doing violence to the theories and that these frameworks give different kinds of results regarding the religious relevance of CSR theories.

The Problem of Implementation and its Relation to the Philosophy of Cognitive Science

According to certain arguments, computation is observer-relative either in the sense that many physical systems implement many computations (Hilary Putnam), or in the sense that almost all physical systems implement all computations (John Searle). If sound, these arguments have a potentially devastating consequence for the computational theory of mind: if arbitrary physical systems can be seen to implement arbitrary computations, the notion of computation seems to lose all explanatory power as far as brains and minds are concerned. David Chalmers and B. Jack Copeland have attempted to counter these relativist arguments by placing certain constraints on the definition of implementation. In this thesis, I examine their proposals and find both wanting in some respects. During the course of this examination, I give a formal definition of the class of combinatorial-state automata , upon which Chalmers s account of implementation is based. I show that this definition implies two theorems (one an observation due to Curtis Brown) concerning the computational power of combinatorial-state automata, theorems which speak against founding the theory of implementation upon this formalism. Toward the end of the thesis, I sketch a definition of the implementation of Turing machines in dynamical systems, and offer this as an alternative to Chalmers s and Copeland s accounts of implementation. I demonstrate that the definition does not imply Searle s claim for the universal implementation of computations. However, the definition may support claims that are weaker than Searle s, yet still troubling to the computationalist. There remains a kernel of relativity in implementation at any rate, since the interpretation of physical systems seems itself to be an observer-relative matter, to some degree at least. This observation helps clarify the role the notion of computation can play in cognitive science. Specifically, I will argue that the notion should be conceived as an instrumental rather than as a fundamental or foundational one.

The goals of cognitive science

In this paper cognitive science is defined as the study of intelligence as a computational process. The several disciplines which contribute to the study of cognitive science are briefly described so as to glean a birds-eye view of the subject of cognitive science.

Artificial Intelligence and Cognitive Science

Editorial for 17th AICS Conference