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 428
... Lagnado for providing the data analysed in this chapter , and Paul Cairns and Nathaniel Daw for helpful com- ments on a previous version of this manuscript . References Anderson , J. R. ( 1990 ) . The adaptive character of thought ...
... Lagnado for providing the data analysed in this chapter , and Paul Cairns and Nathaniel Daw for helpful com- ments on a previous version of this manuscript . References Anderson , J. R. ( 1990 ) . The adaptive character of thought ...
Page 482
... Lagnado , D. A. , & Waldmann , M. R ( 2007 ) . Causal reasoning through intervention . In A. Gopnik & L. E. Schultz ( Eds . ) , Causal learning : Psychology , phi- losophy , and computation ( pp . 86–100 ) . Oxford University Press ...
... Lagnado , D. A. , & Waldmann , M. R ( 2007 ) . Causal reasoning through intervention . In A. Gopnik & L. E. Schultz ( Eds . ) , Causal learning : Psychology , phi- losophy , and computation ( pp . 86–100 ) . Oxford University Press ...
Page 499
... Lagnado , D. , & Sloman , S.A. ( 2004 ) . The advantage of timely intervention . Journal of Experimental Psychology : Learning , Memory , and Cognition , 30 , 856–876 . Lagnado , D. , & Sloman , S. A. ( 2006 ) . Time as a guide to cause ...
... Lagnado , D. , & Sloman , S.A. ( 2004 ) . The advantage of timely intervention . Journal of Experimental Psychology : Learning , Memory , and Cognition , 30 , 856–876 . Lagnado , D. , & Sloman , S. A. ( 2006 ) . Time as a guide to cause ...
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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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