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
... particular level of realist commitment to theoretical elements , while rational analysis is a tool by which to develop the theories . No close connection between rational analyses and a particular level of description is warranted , and ...
... particular level of realist commitment to theoretical elements , while rational analysis is a tool by which to develop the theories . No close connection between rational analyses and a particular level of description is warranted , and ...
Page 129
... particular constructions . This means that other constraining information would continue to be useful ( see also ... particular , grammatical construction . Hence , he concludes the child would have to do one of two things : If he or she ...
... particular constructions . This means that other constraining information would continue to be useful ( see also ... particular , grammatical construction . Hence , he concludes the child would have to do one of two things : If he or she ...
Page 360
... particular target and the known values of the prime and noise ; it is this last term that enacts explaining away . For the particular task of forced choice testing , the situation is further simplified by taking ( 3 ) as calculated for ...
... particular target and the known values of the prime and noise ; it is this last term that enacts explaining away . For the particular task of forced choice testing , the situation is further simplified by taking ( 3 ) as calculated for ...
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