Transcription of A Distributional Perspective on Reinforcement Learning
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A Distributional Perspective on Reinforcement Learning
A Distributional Perspective on Reinforcement LearningMarc G. Bellemare* 1 Will Dabney* 1R emi Munos1 AbstractIn this paper we argue for the fundamental impor-tance of thevalue distribution: the distributionof the random return received by a reinforcementlearning agent. This is in contrast to the com-mon approach to Reinforcement Learning whichmodels the expectation of this return, there is an established body of liter-ature studying the value distribution, thus far ithas always been used for a specific purpose suchas implementing risk-aware behaviour. We beginwith theoretical results in both the policy eval-uation and control settings, exposing a signifi-cant Distributional instability in the latter.
A Distributional Perspective on Reinforcement Learning sure theory may think of as the space of all possible outcomes of an experiment (Billingsley,1995).
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