Methods › Reinforcement Learning › Replay Memory › Experience Replay
Experience Replay
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Experience Replay is a replay memory technique used in reinforcement learning where we store the agent’s experiences at each time-step, eₜ = (sₜ, aₜ, rₜ, sₜ₊₁) in a data-set D = e₁, ⋯, e_N , pooled over many episodes into a replay memory. We then usually sample the memory randomly for a minibatch of experience, and use this to learn off-policy, as with Deep Q-Networks. This tackles the problem of autocorrelation leading to unstable training, by making the problem more like a supervised learning problem.
Image Credit: Hands-On Reinforcement Learning with Python, Sudharsan Ravichandiran
Papers archive 2025-07-28
30 shown of 865, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Turning Sand to Gold: Recycling Data to Bridge On-Policy and Off-Policy Learning via Causal Bound 15 Jul 2025 · 0 repositories · arXiv:2507.11269
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Deep Reinforcement Learning with Gradient Eligibility Traces 12 Jul 2025 · 1 repository · arXiv:2507.09087
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Multi-Objective Reinforcement Learning for Cognitive Radar Resource Management 25 Jun 2025 · 0 repositories · arXiv:2506.20853
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CAWR: Corruption-Averse Advantage-Weighted Regression for Robust Policy Optimization 18 Jun 2025 · 1 repository · arXiv:2506.15654
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Reliable Critics: Monotonic Improvement and Convergence Guarantees for Reinforcement Learning 8 Jun 2025 · 0 repositories · arXiv:2506.07134
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Contextual Experience Replay for Self-Improvement of Language Agents 7 Jun 2025 · 0 repositories · arXiv:2506.06698
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Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning 6 Jun 2025 · 1 repository · arXiv:2506.05968Syntology ran 1 of 4 samples · 3 unverified
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A Novel Deep Reinforcement Learning Method for Computation Offloading in Multi-User Mobile Edge Computing with Decentralization 3 Jun 2025 · 0 repositories · arXiv:2506.02458
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FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control 28 May 2025 · 0 repositories · arXiv:2505.22642
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Analyzing Mitigation Strategies for Catastrophic Forgetting in End-to-End Training of Spoken Language Models 23 May 2025 · 0 repositories · arXiv:2505.17496
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LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models 21 May 2025 · 0 repositories · arXiv:2505.15293
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LifelongAgentBench: Evaluating LLM Agents as Lifelong Learners 17 May 2025 · 1 repository · arXiv:2505.11942
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Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents 16 May 2025 · 0 repositories · arXiv:2505.11708
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Electric Bus Charging Schedules Relying on Real Data-Driven Targets Based on Hierarchical Deep Reinforcement Learning 15 May 2025 · 0 repositories · arXiv:2505.10262
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Deep reinforcement learning-based longitudinal control strategy for automated vehicles at signalised intersections 13 May 2025 · 0 repositories · arXiv:2505.08896
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GradMix: Gradient-based Selective Mixup for Robust Data Augmentation in Class-Incremental Learning 13 May 2025 · 0 repositories · arXiv:2505.08528
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Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control 13 May 2025 · 0 repositories · arXiv:2505.09029
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Online Learning-based Adaptive Beam Switching for 6G Networks: Enhancing Efficiency and Resilience 12 May 2025 · 1 repository · arXiv:2505.08032
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Energy Efficient RSMA-Based LEO Satellite Communications Assisted by UAV-Mounted BD-Active RIS: A DRL Approach 7 May 2025 · 0 repositories · arXiv:2505.04148
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A Goal-Oriented Reinforcement Learning-Based Path Planning Algorithm for Modular Self-Reconfigurable Satellites 4 May 2025 · 0 repositories · arXiv:2505.01966
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Approximation to Deep Q-Network by Stochastic Delay Differential Equations 1 May 2025 · 0 repositories · arXiv:2505.00382
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AlphaGrad: Non-Linear Gradient Normalization Optimizer 22 Apr 2025 · 0 repositories · arXiv:2504.16020
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Next-Future: Sample-Efficient Policy Learning for Robotic-Arm Tasks 15 Apr 2025 · 0 repositories · arXiv:2504.11247
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Moderate Actor-Critic Methods: Controlling Overestimation Bias via Expectile Loss 14 Apr 2025 · 0 repositories · arXiv:2504.09929
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Graph Based Deep Reinforcement Learning Aided by Transformers for Multi-Agent Cooperation 11 Apr 2025 · 0 repositories · arXiv:2504.08195
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Proxy-Anchor and EVT-Driven Continual Learning Method for Generalized Category Discovery 11 Apr 2025 · 1 repository · arXiv:2504.08550
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Neuron-level Balance between Stability and Plasticity in Deep Reinforcement Learning 9 Apr 2025 · 0 repositories · arXiv:2504.08000
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Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation 1 Apr 2025 · 0 repositories · arXiv:2504.00420
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Dynamic Operating System Scheduling Using Double DQN: A Reinforcement Learning Approach to Task Optimization 31 Mar 2025 · 0 repositories · arXiv:2503.23659
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Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off 30 Mar 2025 · 1 repository · arXiv:2503.23390
Tasks archive 2025-07-28
20 shown of 289 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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