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Distributional Reinforcement Learning

Value distribution is the distribution of the random return received by a reinforcement learning agent. it been used for a specific purpose such as implementing risk-aware behaviour.

We have random return Z whose expectation is the value Q. This random return is also described by a recursive equation, but one of a distributional nature

Papers

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Showing 131–137 of 137 papers

Title	Date	Tasks	Status
EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning	Aug 22, 2024	Distributional Reinforcement Learningquantile regression	CodeCode Available
Information-Directed Exploration for Deep Reinforcement Learning	Dec 18, 2018	Atari GamesDeep Reinforcement Learning	CodeCode Available
A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement Learning	Jan 4, 2024	Atari GamesDistributional Reinforcement Learning	CodeCode Available
Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State Observations	Sep 17, 2021	Density EstimationDistributional Reinforcement Learning	CodeCode Available
RIZE: Regularized Imitation Learning via Distributional Reinforcement Learning	Feb 27, 2025	Distributional Reinforcement LearningImitation Learning	CodeCode Available
Two steps to risk sensitivity	Nov 12, 2021	Decision MakingDistributional Reinforcement Learning	CodeCode Available
Variance Control for Distributional Reinforcement Learning	Jul 30, 2023	Distributional Reinforcement LearningMuJoCo	CodeCode Available

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