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Science / Machine learning / Rescorla–Wagner model / Classical conditioning / Mark A. Gluck / Pattern recognition / Blocking effect / Learning / Behavior / Cognitive science


Document Date: 2011-07-19 14:12:18

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File Size: 3,13 MB

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Company

American PsychologicalAssociation Inc. / /

Country

Netherlands / United States / /

Currency

USD / /

Facility

National Institute of Mental Health / Stanford University / Jordan Hall / /

IndustryTerm

adaptive networks / information-processing potential / information processing / neuronlike computing elements / multilayered networks / associative network / adaptive network / food / perceptron convergence algorithm / parallel distributed processing / information-processing capabilities / e-~ / learning algorithm / focused on exploring the information-processing potential / /

MedicalCondition

particular disease / common disease / fictitious diseases / certain diseases / alternate diseases / alternative diseases / electric shock / disease / shock / rare disease / LEARNING one disease / mutually exclusive disease / diseases / each disease / stomach cramps / /

Organization

Sloan Foundation / National Science Foundation / Department of Psychology / Stanford University / National Institute of Mental Health / /

Person

Misha Pavel / Jay McClelland / Nelson Donegan / Robert Nosofsky / Robert Kylberg / Rescorla / Naomi Schechter / Richard Thompson / Thom Deaton / Experimental Psychology / Daniel Kahneman / Gus Larsson / Roger Shepard / Andy Barto / Amos Tversky / Jamie Uyehara / Andrea Gallagher / Susanna Lee / Mike McClosky / Carrie Henderson / Gordon H. Bower / Mark A. Gluck / Van Henkle / David Parker / Paul Rosenbloom / Anthony Henin / Richard Sutton / /

Position

General / representative / Adaptive Network Model / /

ProgrammingLanguage

E / /

ProvinceOrState

California / /

SportsLeague

Stanford University / /

Technology

speech recognition / learning algorithm / artificial intelligence / perceptron convergence algorithm / LMS algorithms / /

SocialTag