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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 51–100 of 137 papers

TitleStatusHype
Robustness and risk management via distributional dynamic programming—0
Robust Probabilistic Model Checking with Continuous Reward Domains—0
Robust Reinforcement Learning with Distributional Risk-averse formulation—0
Safe Distributional Reinforcement Learning—0
Sample-based Distributional Policy Gradient—0
Second-Order Bounds for [0,1]-Valued Regression via Betting Loss—0
SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement Learning—0
Statistical Efficiency of Distributional Temporal Difference Learning and Freedman's Inequality in Hilbert Spaces—0
Statistics and Samples in Distributional Reinforcement Learning—0
Stochastically Dominant Distributional Reinforcement Learning—0
The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning—0
The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning—0
The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation—0
Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning—0
The Benefits of Being Categorical Distributional: Uncertainty-aware Regularized Exploration in Reinforcement Learning—0
Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm—0
Uncertainty-Aware Transient Stability-Constrained Preventive Redispatch: A Distributional Reinforcement Learning Approach—0
Distributional Perturbation for Efficient Exploration in Distributional Reinforcement Learning—0
Distributional Reinforcement Learning-based Energy Arbitrage Strategies in Imbalance Settlement Mechanism—0
Distributional Reinforcement Learning for Efficient Exploration—0
Distributional Reinforcement Learning for Risk-Sensitive Policies—0
Distributional Reinforcement Learning for mmWave Communications with Intelligent Reflectors on a UAV—0
Distributional Reinforcement Learning for Scheduling of Chemical Production Processes—0
Distributional Reinforcement Learning on Path-dependent Options—0
Distributional reinforcement learning with linear function approximation—0
Distributional Reinforcement Learning with Ensembles—0
Distributional Reinforcement Learning with Monotonic Splines—0
Distributional Reinforcement Learning with Dual Expectile-Quantile Regression—0
Distributional Reinforcement Learning with Online Risk-awareness Adaption—0
Diverse Projection Ensembles for Distributional Reinforcement Learning—0
Exploration by Distributional Reinforcement Learning—0
Exploration with Multi-Sample Target Values for Distributional Reinforcement Learning—0
Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations—0
A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation—0
Flow Models for Unbounded and Geometry-Aware Distributional Reinforcement Learning—0
Foundations of Multivariate Distributional Reinforcement Learning—0
GAN-powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing—0
A Simulation Environment and Reinforcement Learning Method for Waste Reduction—0
Hedging and Pricing Structured Products Featuring Multiple Underlying Assets—0
How Does Return Distribution in Distributional Reinforcement Learning Help Optimization?—0
Improving Robustness via Risk Averse Distributional Reinforcement Learning—0
Improving the generalizability and robustness of large-scale traffic signal control—0
Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems—0
Invariance to Quantile Selection in Distributional Continuous Control—0
Is Risk-Sensitive Reinforcement Learning Properly Resolved?—0
Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning—0
Millimeter Wave Communications with an Intelligent Reflector: Performance Optimization and Distributional Reinforcement Learning—0
Minimizing Safety Interference for Safe and Comfortable Automated Driving with Distributional Reinforcement Learning—0
MMD-MIX: Value Function Factorisation with Maximum Mean Discrepancy for Cooperative Multi-Agent Reinforcement Learning—0
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning—0
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