Premium
Naive Reinforcement Learning With Endogenous Aspirations
Author(s) -
Börgers Tilman,
Sarin Rajiv
Publication year - 2000
Publication title -
international economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.658
H-Index - 86
eISSN - 1468-2354
pISSN - 0020-6598
DOI - 10.1111/1468-2354.00090
Subject(s) - stochastic game , maximization , reinforcement , reinforcement learning , feeling , matching (statistics) , economics , microeconomics , simple (philosophy) , mathematical economics , psychology , social psychology , computer science , artificial intelligence , mathematics , statistics , philosophy , epistemology
This article considers a simple model of reinforcement learning. All behavior change derives from the reinforcing or deterring effect of instantaneous payoff experiences. Payoff experiences are reinforcing or deterring depending on whether the payoff exceeds an aspiration level or falls short of it. Over time, the aspiration level is adjusted toward the actually experienced payoffs. This article shows that aspiration level adjustments may improve the decision maker's long‐run performance by preventing him or her from feeling dissatisfied with even the best available strategies. However, such movements also lead to persistent deviations from expected payoff maximization by creating ‘probability matching’ effects.