Reasoning as simulation

The theory that human cognition proceeds through mental simulations, if true, would provide a parsimonious explanation of how the mechanisms of reasoning and problem solving integrate with and develop from mechanisms underlying forms of cognition that occur earlier in evolution and development. Howe...

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Bibliographic Details
Published in:Cognitive processing 2009-11, Vol.10 (4), p.343-353
Main Authors: Cassimatis, Nicholas L., Murugesan, Arthi, Bignoli, Perrin G.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Behavioral Sciences
Biological and medical sciences
Biomedical and Life Sciences
Biomedicine
Cognition - physiology
Cognition. Intelligence
Concept Formation - physiology
Decision Making - physiology
Fundamental and applied biological sciences. Psychology
Humans
Logic
Models, Psychological
Neurosciences
Perception - physiology
Problem Solving - physiology
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Reasoning. Problem solving
Research Report
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Summary:The theory that human cognition proceeds through mental simulations, if true, would provide a parsimonious explanation of how the mechanisms of reasoning and problem solving integrate with and develop from mechanisms underlying forms of cognition that occur earlier in evolution and development. However, questions remain about whether simulation mechanisms are powerful enough to exhibit human-level reasoning and inference. In order to investigate this issue, we show that it is possible to characterize some of the most powerful modern artificial intelligence algorithms for logical and probabilistic inference as methods of simulating alternate states of the world. We show that a set of specific human perceptual mechanisms, even if not implemented using mechanisms described in artificial intelligence, can nevertheless perform the same operations as those algorithms. Although this result does not demonstrate that simulation theory is true, it does show that whatever mechanisms underlie perception have at least as much power to explain non-perceptual human reasoning and problem solving as some of the most powerful known algorithms.
ISSN:1612-4782
1612-4790
DOI:10.1007/s10339-009-0256-0