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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 81–90 of 137 papers

TitleStatusHype
IGN : Implicit Generative NetworksCode0
A Simulation Environment and Reinforcement Learning Method for Waste Reduction—0
Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems—0
Distributional Reinforcement Learning for Scheduling of Chemical Production Processes—0
Exploration with Multi-Sample Target Values for Distributional Reinforcement Learning—0
Distributional Reinforcement Learning with Regularized Wasserstein LossCode0
On solutions of the distributional Bellman equation—0
Conservative Distributional Reinforcement Learning with Safety Constraints—0
Robustness and risk management via distributional dynamic programming—0
Conjugated Discrete Distributions for Distributional Reinforcement LearningCode0
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