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BEGIN:VEVENT
UID:a86cc0b8f08e092659f815e4c34e4ed4
CATEGORIES:Seminars
CREATED:20250611T052756
SUMMARY:Lunch Seminar: Cosmin Ilut - Duke University
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:<p><em><strong>Learning Optimal Behavior Through Reasoning and Experiences<
 /strong></em></p><p>Abstract:</p><p style="text-align: justify;">We develop
  a novel framework of bounded rationality under cognitive frictions that st
 udies learning over optimal behavior through both deliberative reasoning an
 d accumulated experiences. Using both types of information, agents engage i
 n Bayesian non-parametric estimation of the unknown action value function. 
 Reasoning signals are produced internally through mental deliberation, subj
 ect to a cognitive cost. Experience signals are based on the observed utili
 ty outcomes at previous actions. Agents' subjective estimation uncertainty,
  which evolves through information accumulation, modulates the two modes of
  learning in a state- and history-dependent way. We discuss how the model d
 raws on and bridges conceptual, methodological and empirical insights from 
 both economics and the cognitive sciences literature on reinforcement learn
 ing.</p>
DTSTAMP:20260504T141859Z
DTSTART:20250703T130000Z
DTEND:20250703T140000Z
SEQUENCE:0
TRANSP:OPAQUE
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