The Probabilistic Mind: Prospects for Bayesian Cognitive ScienceNick Chater, Mike Oaksford The 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 methods. It synthesizes and evaluates the progress in the past decade, taking into account developments in Bayesian statistics, statistical analysis of the cognitive 'environment' and a variety of theoretical and experimental lines of research. The scope of the book is broad, covering important recent work in reasoning, decision making, categorization, and memory. Including chapters from many of the leading figures in this field, The Probabilistic Mind will be valuable for psychologists and philosophers interested in cognition. |
From inside the book
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Page 60
... analysis implies that the use of rational analyses is entirely orthogonal to the level of description for a theory . The level of description dictates a particular level of realist commitment to theoretical elements , while rational ...
... analysis implies that the use of rational analyses is entirely orthogonal to the level of description for a theory . The level of description dictates a particular level of realist commitment to theoretical elements , while rational ...
Page 68
Prospects for Bayesian Cognitive Science Nick Chater, Mike Oaksford. of rational analysis at the computational level . As just one example , Take - the - Best , combined with the Recognition Heuristic , provides a mechanism explanation ...
Prospects for Bayesian Cognitive Science Nick Chater, Mike Oaksford. of rational analysis at the computational level . As just one example , Take - the - Best , combined with the Recognition Heuristic , provides a mechanism explanation ...
Page 485
... rational analysis : an assessment of causal reasoning and learning Steven Sloman and Philip M. Fernbach Brown University , Providence , RI , USA Our goal in this chapter is a rational analysis of human causal reasoning and learning . We ...
... rational analysis : an assessment of causal reasoning and learning Steven Sloman and Philip M. Fernbach Brown University , Providence , RI , USA Our goal in this chapter is a rational analysis of human causal reasoning and learning . We ...
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 |
Common terms and phrases
algorithm alternative analysis approach approximate argument associated assumed assumption attribute Bayesian behavior beliefs Cambridge causal cause Chater choice cluster cognitive complexity computational concept conditional consider correlation decision depends described developed distribution effect environment estimate et al evidence example expected experience experimental explain framing function given heuristic human hypothesis important individual inference involved Journal judgment language learning logic mean memory methods natural normative Oaksford objects observed optimal options outcomes parameters participants particular performance possible posterior predictions present Press principle prior probabilistic probability problem produce prospect Psychological question rational rational analysis reasoning reference relation relative represent representation require response Review rule sample Science selection semantic shows similar simple statistical structure subjective suggest task theory tion trials University utility variables weight