Acta Biotheoretica 58 (2):191-216 (2010)
How can an incomplete and uncertain model of the environment be used to perceive, infer, decide and act efficiently? This is the challenge that both living and artificial cognitive systems have to face. Symbolic logic is, by its nature, unable to deal with this question. The subjectivist approach to probability is an extension to logic that is designed specifically to face this challenge. In this paper, we review a number of frequently encountered cognitive issues and cast them into a common Bayesian formalism. The concepts we review are ambiguities, fusion, multimodality, conflicts, modularity, hierarchies and loops. First, each of these concepts is introduced briefly using some examples from the neuroscience, psychophysics or robotics literature. Then, the concept is formalized using a template Bayesian model. The assumptions and common features of these models, as well as their major differences, are outlined and discussed.
|Keywords||Philosophy Evolutionary Biology Philosophy of Biology|
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A Bayesian Perspective on Magnitude Estimation.Frederike H. Petzschner, Stefan Glasauer & Klaas E. Stephan - 2015 - Trends in Cognitive Sciences 19 (5):285-293.
Integrate, Yes, but What and How? A Computational Approach of Sensorimotor Fusion in Speech.Raphaël Laurent, Clément Moulin-Frier, Pierre Bessière, Jean-Luc Schwartz & Julien Diard - 2013 - Behavioral and Brain Sciences 36 (4):364 - 365.
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