Researcheligibility tracetabular learningcredit assignmentsequential delays
Information Uncertainty Influences Learning Strategy From Delayed Rewards
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Relevance ScoreResearchers Alec Solway, Caroline J. Charpentier, and Sean R. Maulhardt publish on February 2, 2026, describing a behavioral experiment (N=142) that probed temporal credit assignment by combining sequentially delayed rewards, intervening events, and varying feedback information. They developed and compared two computational strategies—eligibility trace and tabular updates—and report that lower information uncertainty led participants to favor tabular updates, improving prediction accuracy and credit assignment.
