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. 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.
Cassimatis
Nicholas L
NL
Rensselaer Polytechnic Institute, Troy, NY, USA. cassin@rpi.edu
Murugesan
Arthi
A
Bignoli
Perrin G
PG
D000465:Algorithms; D001185:Artificial Intelligence; D003071:Cognition / Q000502:physiology*; D003210:Concept Formation / Q000502:physiology; D003657:Decision Making / Q000502:physiology; D006801:Humans; D008128:Logic; D008960:Models, Psychological; D010465:Perception / Q000502:physiology*; D011340:Problem Solving / Q000502:physiology