Policy Gradient Methods

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 103 papers with code (382 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.

• Proximal Policy Optimization Algorithms
  20 Jul 2017 188 repositories listed Syntology ran 99 of 176 samples · 77 unverified · 94 pointer-only (licence)
  We propose a new family of policy gradient methods for reinforcement learning, which alternate between sampling data through interaction with the environment, and optimizing a "surrogate" objective function using…
• Self-critical Sequence Training for Image Captioning
  2 Dec 2016 31 repositories listed Syntology ran 8 of 13 samples · 5 unverified · 3 pointer-only (licence)
  In this paper we consider the problem of optimizing image captioning systems using reinforcement learning, and show that by carefully optimizing our systems using the test metrics of the MSCOCO task, significant gains…
• Trust Region Policy Optimization
  19 Feb 2015 24 repositories listed Syntology ran 7 of 17 samples · 10 unverified · 7 pointer-only (licence)
  We describe an iterative procedure for optimizing policies, with guaranteed monotonic improvement.
• High-Dimensional Continuous Control Using Generalized Advantage Estimation
  8 Jun 2015 17 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Policy gradient methods are an appealing approach in reinforcement learning because they directly optimize the cumulative reward and can straightforwardly be used with nonlinear function approximators such as neural…
• Deep Reinforcement Learning for Dialogue Generation
  5 Jun 2016 8 repositories listed
  Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time while ignoring their influence on…
• Competitive Policy Optimization
  18 Jun 2020 4 repositories listed Syntology ran 0 of 5 samples · 5 unverified · 1 pointer-only (licence)
  A core challenge in policy optimization in competitive Markov decision processes is the design of efficient optimization methods with desirable convergence and stability properties.
• Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization
  3 Oct 2022 3 repositories listed
  To help answer this, we first introduce an open-source modular library, RL4LMs (Reinforcement Learning for Language Models), for optimizing language generators with RL.
• Distributional Policy Optimization: An Alternative Approach for Continuous Control
  23 May 2019 3 repositories listed
  We show that optimizing over such sets results in local movement in the action space and thus convergence to sub-optimal solutions.
• Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models
  23 Feb 2019 3 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  Defining action spaces for conversational agents and optimizing their decision-making process with reinforcement learning is an enduring challenge.
• Reevaluating Policy Gradient Methods for Imperfect-Information Games
  13 Feb 2025 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  In the past decade, motivated by the putative failure of naive self-play deep reinforcement learning (DRL) in adversarial imperfect-information games, researchers have developed numerous DRL algorithms based on…
• Policy Gradient Methods in the Presence of Symmetries and State Abstractions
  9 May 2023 2 repositories listed
  Our policy gradient results allow for leveraging approximate symmetries of the environment for policy optimization.
• Experimental design for MRI by greedy policy search
  30 Oct 2020 2 repositories listed Syntology ran 4 of 18 samples · 14 unverified
  In today's clinical practice, magnetic resonance imaging (MRI) is routinely accelerated through subsampling of the associated Fourier domain.
• Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting
  14 Jul 2020 2 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  Policy gradient methods have shown success in learning control policies for high-dimensional dynamical systems.
• Deep Reinforcement Learning Algorithm for Dynamic Pricing of Express Lanes with Multiple Access Locations
  10 Sep 2019 2 repositories listed
  This article develops a deep reinforcement learning (Deep-RL) framework for dynamic pricing on managed lanes with multiple access locations and heterogeneity in travelers' value of time, origin, and destination.
• Shapley Q-value: A Local Reward Approach to Solve Global Reward Games
  11 Jul 2019 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  To deal with this problem, we i) introduce a cooperative-game theoretical framework called extended convex game (ECG) that is a superset of global reward game, and ii) propose a local reward approach called Shapley…
• Ekar: An Explainable Method for Knowledge Aware Recommendation
  22 Jun 2019 2 repositories listed
  Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations.
• Trajectory-Based Off-Policy Deep Reinforcement Learning
  14 May 2019 2 repositories listed
  Policy gradient methods are powerful reinforcement learning algorithms and have been demonstrated to solve many complex tasks.
• On-Policy Trust Region Policy Optimisation with Replay Buffers
  18 Jan 2019 2 repositories listed
  Building upon the recent success of deep reinforcement learning methods, we investigate the possibility of on-policy reinforcement learning improvement by reusing the data from several consecutive policies.
• Remember and Forget for Experience Replay
  16 Jul 2018 2 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  ER recalls experiences from past iterations to compute gradient estimates for the current policy, increasing data-efficiency.
• Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents
  18 Dec 2017 2 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  Evolution strategies (ES) are a family of black-box optimization algorithms able to train deep neural networks roughly as well as Q-learning and policy gradient methods on challenging deep reinforcement learning (RL)…
• Action-depedent Control Variates for Policy Optimization via Stein's Identity
  30 Oct 2017 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Policy gradient methods have achieved remarkable successes in solving challenging reinforcement learning problems.
• Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
  7 Nov 2016 2 repositories listed
  We analyze the connection between Q-Prop and existing model-free algorithms, and use control variate theory to derive two variants of Q-Prop with conservative and aggressive adaptation.
• Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models
  5 May 2025 1 repository listed
  We propose a direct retrieval-augmented optimization framework, named DRO, that enables end-to-end training of two key components: (i) a generative knowledge selection model and (ii) an LLM generator.
• Hierarchical Policy-Gradient Reinforcement Learning for Multi-Agent Shepherding Control of Non-Cohesive Targets
  3 Apr 2025 1 repository listed
  We propose a decentralized reinforcement learning solution for multi-agent shepherding of non-cohesive targets using policy-gradient methods.
• Convergence Guarantees of Model-free Policy Gradient Methods for LQR with Stochastic Data
  27 Feb 2025 1 repository listed
  After briefly summarizing the state of the art for cases with a known model, we focus on scenarios where the system dynamics are unknown, and approximate gradient information is obtained using zeroth-order optimization…
• Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods
  3 Feb 2025 1 repository listed Syntology ran 1 of 8 samples · 7 unverified
  Discrete diffusion models have recently gained significant attention due to their ability to process complex discrete structures for language modeling.
• Divergence-Augmented Policy Optimization
  25 Jan 2025 1 repository listed
  In deep reinforcement learning, policy optimization methods need to deal with issues such as function approximation and the reuse of off-policy data.
• An Attentive Graph Agent for Topology-Adaptive Cyber Defence
  24 Jan 2025 1 repository listed
  As cyber threats grow increasingly sophisticated, reinforcement learning (RL) is emerging as a promising technique to create intelligent and adaptive cyber defense systems.
• Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning
  8 Jan 2025 1 repository listed
  Reinforcement learning (RL) aims to estimate the action to take given a (time-varying) state, with the goal of maximizing a cumulative reward function.
• Reinforcement Learning: An Overview
  6 Dec 2024 1 repository listed
  This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement learning and sequential decision making, covering value-based methods, policy-based methods, model-based methods, multi-agent…

Syntology lines on 14 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.