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. |
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Page 291
... options receive a higher share than the extreme options and that this effect is larger at high separation ( by 21 % ) . Interestingly , a similar pattern is found in the binary choice ( Experiment 1B ) , where participants chose the option ...
... options receive a higher share than the extreme options and that this effect is larger at high separation ( by 21 % ) . Interestingly , a similar pattern is found in the binary choice ( Experiment 1B ) , where participants chose the option ...
Page 292
... option , and in some of the cases , following the participant's choice , announce that the option chosen is unavailable but a speeded choice is possible ( under deadline ) for one of the other two options . The idea is that , if the ...
... option , and in some of the cases , following the participant's choice , announce that the option chosen is unavailable but a speeded choice is possible ( under deadline ) for one of the other two options . The idea is that , if the ...
Page 293
... option more than they chose the extreme options ( t ( 142 ) = 7.185 , p < 0.001 ) . The fraction of choices made after a first choice , which was an extreme option announced to be unavailable is shown in the right panel . One can see ...
... option more than they chose the extreme options ( t ( 142 ) = 7.185 , p < 0.001 ) . The fraction of choices made after a first choice , which was an extreme option announced to be unavailable is shown in the right panel . One can see ...
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