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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
Intelligent Resource Allocation in Joint Radar-Communication With Graph Neural NetworksCode1
Trust Region-Based Safe Distributional Reinforcement Learning for Multiple ConstraintsCode1
Risk-Sensitive Policy with Distributional Reinforcement LearningCode1
Gamma and Vega Hedging Using Deep Distributional Reinforcement LearningCode1
Unifying Cardiovascular Modelling with Deep Reinforcement Learning for Uncertainty Aware Control of Sepsis TreatmentCode1
Implicit Distributional Reinforcement LearningCode1
Adaptive Risk-Tendency: Nano Drone Navigation in Cluttered Environments with Distributional Reinforcement LearningCode1
A Distributional Analogue to the Successor RepresentationCode1
Distributional Reinforcement Learning via Moment MatchingCode1
Conservative Offline Distributional Reinforcement LearningCode1
Distributional Reinforcement Learning with Unconstrained Monotonic Neural NetworksCode1
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation—0
Flow Models for Unbounded and Geometry-Aware Distributional Reinforcement Learning—0
A Point-Based Algorithm for Distributional Reinforcement Learning in Partially Observable Domains—0
An Analysis of Quantile Temporal-Difference 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
Foundations of Multivariate Distributional Reinforcement Learning—0
A Local Temporal Difference Code for Distributional Reinforcement Learning—0
Adaptive Nesterov Accelerated Distributional Deep Hedging for Efficient Volatility Risk Management—0
Beyond Average Return in Markov Decision Processes—0
Diverse Projection Ensembles for Distributional Reinforcement Learning—0
An Analysis of Categorical Distributional Reinforcement Learning—0
Conservative Distributional Reinforcement Learning with Safety Constraints—0
A Distributional Perspective on Actor-Critic Framework—0
Controlling Synthetic Characters in Simulations: A Case for Cognitive Architectures and Sigma—0
Cramer Type Distances for Learning Gaussian Mixture Models by Gradient Descent—0
An introduction to reinforcement learning for neuroscience—0
CTRLS: Chain-of-Thought Reasoning via Latent State-Transition—0
Deep Distributional Learning with Non-crossing Quantile Network—0
Distributional Reinforcement Learning with Online Risk-awareness Adaption—0
Exploration by Distributional Reinforcement Learning—0
Bayesian Distributional Policy Gradients—0
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation—0
Distributional Reinforcement Learning with Monotonic Splines—0
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning—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
Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space—0
Distributional Reinforcement Learning for Risk-Sensitive Policies—0
Distributional Reinforcement Learning for mmWave Communications with Intelligent Reflectors on a UAV—0
Automatic Risk Adaptation in Distributional Reinforcement Learning—0
Distributional Reinforcement Learning for Scheduling of Chemical Production Processes—0
Distributional Reinforcement Learning on Path-dependent Options—0
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds—0
A Comparative Analysis of Expected and Distributional Reinforcement Learning—0
Distributional reinforcement learning with linear function approximation—0
Distributional Reinforcement Learning with Ensembles—0
Demand-Side Scheduling Based on Multi-Agent Deep Actor-Critic Learning for Smart Grids—0
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