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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BR a B , a B , 4 1 New Events Bol_1 a Bo a BO Objects B B 11-1 It 1 + 1 Observations Fig . 16.6 . A cascaded hidden Markov model that includes a layer for inferring objects based on observations and a second layer for inferring new ...
the backwards causation model is used to build a working memory system and must attempt to satisfy the contradictory goals of maintaining objects while also allowing that new objects enter the buffering system .
fails to faithfully represent previous objects because it does not have a layer above to explain away its representation from objects even further in the past . Figure 16.10 was accomplished with N = 3 ( 4 layers ) .
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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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Other editions - View all
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 |