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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 111–120 of 137 papers

TitleStatusHype
Non-Crossing Quantile Regression for Distributional Reinforcement Learning—0
Distributional Reinforcement Learning for mmWave Communications with Intelligent Reflectors on a UAV—0
Distributional Reinforcement Learning via Moment MatchingCode1
Implicit Distributional Reinforcement LearningCode1
Demand-Side Scheduling Based on Multi-Agent Deep Actor-Critic Learning for Smart Grids—0
Improving Robustness via Risk Averse Distributional Reinforcement Learning—0
Distributional Reinforcement Learning with Ensembles—0
Millimeter Wave Communications with an Intelligent Reflector: Performance Optimization and Distributional Reinforcement Learning—0
Sample-based Distributional Policy Gradient—0
Distributional Reinforcement Learning for Energy-Based Sequential ModelsCode0
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