Model selection in cognitive science as an inverse problem

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5674, Issue , 2005, Pages 219-228

  Myung, Jay I ^a   Pitt, Mark A ^a   Navarro, Daniel J ^b  

^a OHIO STATE UNIVERSITY   (United States)

^b UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Cognitive modeling; Inverse problems; Minimum description length; Model complexity; Model selection; Normalized maximum likelihood; Stochastic complexity

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTER SCIENCE; COMPUTER SIMULATION; CONSTRAINT THEORY; INVERSE PROBLEMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; REDUNDANCY;

COGNITIVE MODELING; MINIMUM DESCRIPTION LENGTH; MODEL COMPLEXITY; MODEL SELECTION; NORMALIZED MAXIMUM LIKELIHOOD; STOCHASTIC COMPLEXITY;

COGNITIVE SYSTEMS;

EID: 21944436678     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.610320     Document Type: Conference Paper

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