Distributional Reinforcement Learning

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Most implemented papers archive 2025-07-28

30 shown of 43 papers with code (137 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Implicit Quantile Networks for Distributional Reinforcement Learning
  14 Jun 2018 19 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  In this work, we build on recent advances in distributional reinforcement learning to give a generally applicable, flexible, and state-of-the-art distributional variant of DQN.
• Distributional Reinforcement Learning with Quantile Regression
  27 Oct 2017 17 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we build on recent work advocating a distributional approach to reinforcement learning in which the distribution over returns is modeled explicitly instead of only estimating the mean.
• Fully Parameterized Quantile Function for Distributional Reinforcement Learning
  5 Nov 2019 6 repositories listed Syntology ran 1 of 10 samples · 9 unverified
  The key challenge in practical distributional RL algorithms lies in how to parameterize estimated distributions so as to better approximate the true continuous distribution.
• Implicit Distributional Reinforcement Learning
  13 Jul 2020 3 repositories listed Syntology ran 4 of 6 samples · 2 unverified
  To improve the sample efficiency of policy-gradient based reinforcement learning algorithms, we propose implicit distributional actor-critic (IDAC) that consists of a distributional critic, built on two deep generator…
• QUOTA: The Quantile Option Architecture for Reinforcement Learning
  5 Nov 2018 3 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  In this paper, we propose the Quantile Option Architecture (QUOTA) for exploration based on recent advances in distributional reinforcement learning (RL).
• Distributional Reinforcement Learning for Multi-Dimensional Reward Functions
  26 Oct 2021 2 repositories listed
  To fully inherit the benefits of distributional RL and hybrid reward architectures, we introduce Multi-Dimensional Distributional DQN (MD3QN), which extends distributional RL to model the joint return distribution from…
• Estimating Risk and Uncertainty in Deep Reinforcement Learning
  23 May 2019 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  Reinforcement learning agents are faced with two types of uncertainty.
• ADDQ: Adaptive Distributional Double Q-Learning
  24 Jun 2025 1 repository listed
  We propose an easy to implement method built on top of distributional reinforcement learning (DRL) algorithms to deal with the overestimation in a locally adaptive way.
• RIZE: Regularized Imitation Learning via Distributional Reinforcement Learning
  27 Feb 2025 1 repository listed
  We introduce a novel Inverse Reinforcement Learning (IRL) approach that overcomes limitations of fixed reward assignments and constrained flexibility in implicit reward regularization.
• Tackling Uncertainties in Multi-Agent Reinforcement Learning through Integration of Agent Termination Dynamics
  21 Jan 2025 1 repository listed
  Multi-Agent Reinforcement Learning (MARL) has gained significant traction for solving complex real-world tasks, but the inherent stochasticity and uncertainty in these environments pose substantial challenges to…
• Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning
  3 Jan 2025 1 repository listed Syntology ran 3 of 4 samples · 1 unverified · 4 pointer-only (licence)
  Additionally, we provide a clear interpretation of the learned policy by leveraging the distribution of returns in DRL and the decomposition of static coherent risk measures.
• EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning
  22 Aug 2024 1 repository listed
  However, these risk measures depend on the accurate estimation of extreme quantiles in the loss distribution's tail, which can be imprecise in QR-based DRL due to the rarity and extremity of tail data, as highlighted in…
• CTD4 -- A Deep Continuous Distributional Actor-Critic Agent with a Kalman Fusion of Multiple Critics
  4 May 2024 1 repository listed
  Categorical Distributional Reinforcement Learning (CDRL) has demonstrated superior sample efficiency in learning complex tasks compared to conventional Reinforcement Learning (RL) approaches.
• A Distributional Analogue to the Successor Representation
  13 Feb 2024 1 repository listed Syntology ran 2 of 4 samples · 2 unverified
  This paper contributes a new approach for distributional reinforcement learning which elucidates a clean separation of transition structure and reward in the learning process.
• Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learning
  11 Feb 2024 1 repository listed
  We present a novel statistical approach to incorporating uncertainty awareness in model-free distributional reinforcement learning involving quantile regression-based deep Q networks.
• Distributional Off-policy Evaluation with Bellman Residual Minimization
  2 Feb 2024 1 repository listed
  In contrast, we study the more manageable expectation-extended statistical distances and provide a novel theoretical justification on their validity for learning the return distribution.
• A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement Learning
  4 Jan 2024 1 repository listed
  Distributional Reinforcement Learning (RL) estimates return distribution mainly by learning quantile values via minimizing the quantile Huber loss function, entailing a threshold parameter often selected heuristically…
• Distributional Bellman Operators over Mean Embeddings
  9 Dec 2023 1 repository listed
  We propose a novel algorithmic framework for distributional reinforcement learning, based on learning finite-dimensional mean embeddings of return distributions.
• Estimation and Inference in Distributional Reinforcement Learning
  29 Sep 2023 1 repository listed Syntology ran 3 of 4 samples · 1 unverified · 4 pointer-only (licence)
  This implies the distributional policy evaluation problem can be solved with sample efficiency.
• Value-Distributional Model-Based Reinforcement Learning
  12 Aug 2023 1 repository listed
  Quantifying uncertainty about a policy's long-term performance is important to solve sequential decision-making tasks.
• Variance Control for Distributional Reinforcement Learning
  30 Jul 2023 1 repository listed
  Although distributional reinforcement learning (DRL) has been widely examined in the past few years, very few studies investigate the validity of the obtained Q-function estimator in the distributional setting.
• Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning
  4 Jul 2023 1 repository listed
  We consider the problem of learning models for risk-sensitive reinforcement learning.
• The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
  25 May 2023 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  In online RL, we propose a DistRL algorithm that constructs confidence sets using maximum likelihood estimation.
• Constrained Reinforcement Learning using Distributional Representation for Trustworthy Quadrotor UAV Tracking Control
  22 Feb 2023 1 repository listed
  We propose a novel, interpretable trajectory tracker integrating a Distributional Reinforcement Learning disturbance estimator for unknown aerodynamic effects with a Stochastic Model Predictive Controller (SMPC).
• Distributional constrained reinforcement learning for supply chain optimization
  3 Feb 2023 1 repository listed
  We introduce Distributional Constrained Policy Optimization (DCPO), a novel approach for reliable constraint satisfaction in RL.
• Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints
  26 Jan 2023 1 repository listed Syntology ran 3 of 4 samples · 1 unverified
  In safety-critical robotic tasks, potential failures must be reduced, and multiple constraints must be met, such as avoiding collisions, limiting energy consumption, and maintaining balance.
• Risk-Sensitive Policy with Distributional Reinforcement Learning
  30 Dec 2022 1 repository listed
  Classical reinforcement learning (RL) techniques are generally concerned with the design of decision-making policies driven by the maximisation of the expected outcome.
• Intelligent Resource Allocation in Joint Radar-Communication With Graph Neural Networks
  17 Oct 2022 1 repository listed
  In this paper, we propose a framework for intelligent vehicles to conduct JRC, with minimal prior knowledge of the system model and a tunable performance balance, in an environment where surrounding vehicles execute…
• IGN : Implicit Generative Networks
  13 Jun 2022 1 repository listed
  In this work, we build recent advances in distributional reinforcement learning to give a state-of-art distributional variant of the model based on the IQN.
• Gamma and Vega Hedging Using Deep Distributional Reinforcement Learning
  10 May 2022 1 repository listed
  We show how D4PG can be used in conjunction with quantile regression to develop a hedging strategy for a trader responsible for derivatives that arrive stochastically and depend on a single underlying asset.

Syntology lines on 11 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.