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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 1–25 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
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