Role of queen promiscuity in reproductive swarming by honey bees

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Bridging the Gap between Theory and Practice of Approximate Bayesian Inference

Contains fulltext : 93772.pdf (preprint version ) (Open Access)ICCM 2012 11th International Conference on Cognitive Modeling, April 16-19, 2012, Berlin, 16 april 201

Psychological models and their distractors

The lack of models in psychology hinders scientific progress. To start addressing this problem, we need a clear understanding of what models are and what they are not

Enactive mechanistic explanation of social cognition

Contains fulltext : 176221.pdf (publisher's version ) (Open Access)In this paper we examine an enactive approach to social cog-nition, a species of radical embodied cognition typically proposed as an alternative to traditional cognitive science. According to enactivists, social cognition is best explained by reference to the social unit rather than the individuals that participate in it. We identify a methodological problem in this approach, namely a lack of clarity with respect to the model of explanation it adopts. We review two complaints about a mechanistic explanatory framework, popular in traditional cognitive science, that prevent enactivists from embracing it. We argue that these complaints are unfounded and propose a conceptual model of enactive mechanistic explanation of social cognition.The 39th Annual Meeting of the Cognitive Science Society (CogSci 2017) (London, UK, 26-29 July 2017

Book review: Hot thought: Mechanisms and applications of emotional coherence [P. Thagard, 2006]

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Counter-factual mathematics of counterfactual predictive models

Contains fulltext : 131491.pdf (publisher's version ) (Open Access)2 p

What does (and doesn’t) make analogical problem solving easy? A complexity-theoretic perspective

Contains fulltext : 99879.pdf (publisher's version ) (Open Access)Solving new problems can be made easier if one can build on experiences with other problems one has already successfully solved. The ability to exploit earlier problem-solving experiences in solving new problems seems to require several cognitive sub-abilities. Minimally, one needs to be able to retrieve relevant knowledge of earlier solved problems and their solutions (solved-exemplar retrieval), to determine whether or not a retrieved problem is sufficient analogous to the problem at hand (analogy derivation), and to infer how the solution-method used for the old problem can be used for the new problem (candidate inference projection). All three processes have successfully been modeled under the framework of Structure-Mapping Theory (SMT). It has long been known that analogy derivation under SMT is computationally intractable, meaning that all (exact) algorithms implementing this ability run impractically long. In this paper we show that the same holds for the other two sub-processes. In sharp contrast to this theoretical intractability, empirical research reveals that in certain situations humans can quickly retrieve appropriate problem-exemplars and quickly make goal-relevant candidate inference projections. How can this speed of processing be explained within the framework of SMT? We consider several possible explanations, both existing and new, and assess their explanatory validity by performing computational-level complexity analyses. Our analyses not only reveal that explanations that have been conjectured to date are incomplete but also identify a set of complete explanations that can guide future empirical research on analogical problem solving.42 p

Parameterized complexity results for a model of theory of mind based on dynamic epistemic logic

Contains fulltext : 163041.pdf (publisher's version ) (Open Access)In this paper we introduce a computational-level model of theory of mind (ToM) based on dynamic epistemic logic (DEL), and we analyze its computational complexity. The model is a special case of DEL model checking. We provide a parameterized complexity analysis, considering several aspects of DEL (e.g., number of agents, size of preconditions, etc.) as parameters. We show that model checking for DEL is PSPACE-hard, also when restricted to single-pointed models and S5 relations, thereby solving an open problem in the literature. Our approach is aimed at formalizing current intractability claims in the cognitive science literature regarding computational models of ToM.18 p

Parameterized complexity in cognitive modeling: Foundations, applications and opportunities

Contains fulltext : 56486.pdf (publisher's version ) (Closed access)In cognitive science, natural cognitive processes are generally conceptualized as computational processes: they serve to transform sensory and mental inputs into mental and action outputs. At the highest level of abstraction, computational models of cognitive processes aim at specifying the computational problem computed by the process under study. Because computational problems are realistic cognitive models only insofar as they can plausibly be computed by the human brain given its limited resources for computation, computational tractability provides a useful constraint on cognitive models. In this paper, we consider the particular benefits of the parameterized complexity framework for identifying sources of intractability in cognitive models. We review existing applications of the parameterized framework to this end in the domains of perception, action and higher cognition. We further identify important opportunities and challenges for future research. These include the development of new methods for complexity analyses specifically tailored to the reverse engineering perspective underlying cognitive science.20 p

Scaling models of cognition to the real world : Complexity-theoretic tools for dealing with intractability

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