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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 1–50 of 137 papers

TitleStatusHype
A Distributional Analogue to the Successor RepresentationCode1
Trust Region-Based Safe Distributional Reinforcement Learning for Multiple ConstraintsCode1
Risk-Sensitive Policy with Distributional Reinforcement LearningCode1
Intelligent Resource Allocation in Joint Radar-Communication With Graph Neural NetworksCode1
Gamma and Vega Hedging Using Deep Distributional Reinforcement LearningCode1
Adaptive Risk-Tendency: Nano Drone Navigation in Cluttered Environments with Distributional Reinforcement LearningCode1
Conservative Offline Distributional Reinforcement LearningCode1
Distributional Reinforcement Learning with Unconstrained Monotonic Neural NetworksCode1
Unifying Cardiovascular Modelling with Deep Reinforcement Learning for Uncertainty Aware Control of Sepsis TreatmentCode1
Distributional Reinforcement Learning via Moment MatchingCode1
Implicit Distributional Reinforcement LearningCode1
Distributional Reinforcement Learning on Path-dependent Options—0
Second-Order Bounds for [0,1]-Valued Regression via Betting Loss—0
CTRLS: Chain-of-Thought Reasoning via Latent State-Transition—0
ADDQ: Adaptive Distributional Double Q-LearningCode0
A Point-Based Algorithm for Distributional Reinforcement Learning in Partially Observable Domains—0
Flow Models for Unbounded and Geometry-Aware Distributional Reinforcement Learning—0
Deep Distributional Learning with Non-crossing Quantile Network—0
Offline and Distributional Reinforcement Learning for Wireless Communications—0
RIZE: Regularized Imitation Learning via Distributional Reinforcement LearningCode0
Adaptive Nesterov Accelerated Distributional Deep Hedging for Efficient Volatility Risk Management—0
A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation—0
Robust Probabilistic Model Checking with Continuous Reward Domains—0
Tackling Uncertainties in Multi-Agent Reinforcement Learning through Integration of Agent Termination DynamicsCode0
Risk-averse policies for natural gas futures trading using distributional reinforcement learning—0
Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement LearningCode0
Hedging and Pricing Structured Products Featuring Multiple Underlying Assets—0
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning—0
Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space—0
Offline and Distributional Reinforcement Learning for Radio Resource Management—0
Foundations of Multivariate Distributional Reinforcement Learning—0
EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement LearningCode0
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation—0
On Policy Evaluation Algorithms in Distributional Reinforcement Learning—0
PG-Rainbow: Using Distributional Reinforcement Learning in Policy Gradient Methods—0
Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence—0
CTD4 -- A Deep Continuous Distributional Actor-Critic Agent with a Kalman Fusion of Multiple CriticsCode0
Statistical Efficiency of Distributional Temporal Difference Learning and Freedman's Inequality in Hilbert Spaces—0
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation—0
Uncertainty-Aware Transient Stability-Constrained Preventive Redispatch: A Distributional Reinforcement Learning Approach—0
Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model—0
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning—0
Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement LearningCode0
Distributional Off-policy Evaluation with Bellman Residual MinimizationCode0
A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement LearningCode0
Distributional Reinforcement Learning-based Energy Arbitrage Strategies in Imbalance Settlement Mechanism—0
Noise Distribution Decomposition based Multi-Agent Distributional Reinforcement Learning—0
Distributional Bellman Operators over Mean EmbeddingsCode0
An introduction to reinforcement learning for neuroscience—0
Beyond Average Return in Markov Decision Processes—0
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