Deictic Option Schemas

IJCAI(2007)

引用 25|浏览9
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摘要
Deictic representation is a representational paradigm, based on selective attention and point- ers, that allows an agent to learn and reason about rich complex environments. In this article we present a hierarchical reinforcement learning framework that employs aspects of deictic repre- sentation. We also present a Bayesian algorithm for learning the correct representation for a given sub-problem and empirically validate it on a complex game environment.
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关键词
hierarchical reinforcement,deictic option schema,bayesian algorithm,empirically validate,selective attention,complex game environment,deictic representation,rich complex environment,representational paradigm,correct representation,reinforcement learning
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