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A DECISION MODEL FOR STEADY‐STATE CHOICE IN CONCURRENT CHAINS
Author(s) -
Christensen Darren R.,
Grace Randolph C.
Publication year - 2010
Publication title -
journal of the experimental analysis of behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.75
H-Index - 61
eISSN - 1938-3711
pISSN - 0022-5002
DOI - 10.1901/jeab.2010.94-227
Subject(s) - reinforcement , decision model , value (mathematics) , goodness of fit , expression (computer science) , steady state (chemistry) , computer science , reinforcement learning , psychology , social psychology , statistics , econometrics , mathematics , artificial intelligence , machine learning , programming language , chemistry
Grace and McLean (2006) proposed a decision model for acquisition of choice in concurrent chains which assumes that after reinforcement in a terminal link, subjects make a discrimination whether the preceding reinforcer delay was short or long relative to a criterion. Their model was subsequently extended by Christensen and Grace (2008, 2009a, 2009b) to include effects of initial‐ and terminal‐link duration on choice. We show that an expression for steady‐state responding can be derived from the decision model, which enables a model for choice that provides an account of archival data that is equal or superior to the contextual choice model (Grace, 1994) and hyperbolic value‐added model (Mazur, 2001) in terms of goodness of fit, parsimony, and parameter invariance. The success of the steady‐state decision model validates the strategy of understanding acquisition phenomena as a bridge toward explaining choice at the molar level.