The Probabilistic Mind: Prospects for Bayesian Cognitive ScienceThe rational analysis method, first proposed by John R. Anderson, has been enormously influential in helping us understand high-level cognitive processes. The Probabilistic Mind is a follow-up to the influential and highly cited 'Rational Models of Cognition' (OUP, 1998). It brings together developments in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian The Probabilistic Mind will be valuable for psychologists and philosophers interested in cognition. |
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A more general objection to the probabilistic approach to cognition , which we have touched on already , is the complexity of the approach . In one sense , the probabilistic approach is elegantly simple — we need simply assign prior ...
For instance , when considering the role of compression , an interpretation of the rational principle of induction by minimum description length ( MDL ) , Feldman ( 2003 ) argues that the neglect of complexity in concept learning has ...
complexity 1 , while ( f2 ( x ) = 0 ) = ( ( x ) = 1 ) has complexity 2. ) The weight of formulae with complexity C is the total probability under the posterior of such formulae : Σ P ( F | W , l ( Obs ) ) .
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Contents
prospects for a Bayesian cognitive science | 3 |
A primer on probabilistic inference | 33 |
Rational analyses instrumentalism and implementations | 59 |
Copyright | |
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The Probabilistic Mind: Prospects for Bayesian Cognitive Science Nick Chater,Mike Oaksford Limited preview - 2008 |
The Probabilistic Mind: Prospects for Bayesian Cognitive Science Nick Chater,Mike Oaksford No preview available - 2008 |