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Some Considerations on Learning to Explore via Meta-Reinforcement Learning

arXiv 1803.01118 ↗First posted 3 Mar 2018cs.AIcited by 44

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Abstract (arXiv)

We consider the problem of exploration in meta reinforcement learning. Two new meta reinforcement learning algorithms are suggested: E-MAML and E-RL2. Results are presented on a novel environment we call `Krazy World' and a set of maze environments. We show E-MAML and E-RL2 deliver better performance on tasks where exploration is important.

Key facts. Cited by 44 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Mar 2018.

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Citing papers per year: 2019: 1; 2020: 0; 2021: 12; 2022: 8; 2023: 8; 2024: 6; 2025: 6; 2026: 3.

44 papers.

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  1. 2023Human-Timescale Adaptation in an Open-Ended Task Spacecited by 138
  2. 2025Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuningcited by 123
  3. 2025Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thoughtcited by 109
  4. 2021A Survey of Exploration Methods in Reinforcement Learningcited by 73
  5. 2024Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Datacited by 63
  6. 2023XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAXcited by 55
  7. 2021Bootstrapped Meta-Learningcited by 45
  8. 2023AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agentscited by 41
  9. 2021Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agentscited by 36
  10. 2022Robust Task Representations for Offline Meta-Reinforcement Learning via Contrastive Learningcited by 35
  11. 2019Watch, Try, Learn: Meta-Learning from Demonstrations and Rewardcited by 28
  12. 2025Meta-RL Induces Exploration in Language Agentscited by 21
32 more
  1. 2024In-context Exploration-Exploitation for Reinforcement Learningcited by 16
  2. 2021CoMPS: Continual Meta Policy Searchcited by 15
  3. 2024AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformerscited by 15
  4. 2021Context Meta-Reinforcement Learning via Neuromodulationcited by 11
  5. 2023Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learningcited by 10
  6. 2021Improving Context-Based Meta-Reinforcement Learning with Self-Supervised Trajectory Contrastive Learningcited by 9
  7. 2021Meta-Reinforcement Learning by Tracking Task Non-stationaritycited by 8
  8. 2021Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RLcited by 8
  9. 2026Meta-Reinforcement Learning with Self-Reflection for Agentic Searchcited by 8
  10. 2021On the Practical Consistency of Meta-Reinforcement Learning Algorithmscited by 6
  11. 2021Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluationcited by 5
  12. 2022Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Taskscited by 5
  13. 2022An Investigation of the Bias-Variance Tradeoff in Meta-Gradientscited by 5
  14. 2021Hindsight Foresight Relabeling for Meta-Reinforcement Learningcited by 4
  15. 2023Meta-Reinforcement Learning via Exploratory Task Clusteringcited by 4
  16. 2023First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offscited by 4
  17. 2022Variational Meta Reinforcement Learning for Social Roboticscited by 3
  18. 2022Meta Reinforcement Learning with Successor Feature Based Contextcited by 3
  19. 2024Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparatorcited by 2
  20. 2022On the Convergence Theory of Meta Reinforcement Learning with Personalized Policiescited by 1
  21. 2022Enhanced Meta Reinforcement Learning using Demonstrations in Sparse Reward Environmentscited by 1
  22. 2023Meta Generative Flow Networks with Personalization for Task-Specific Adaptationcited by 1
  23. 2024Memory Sequence Length of Data Sampling Impacts the Adaptation of Meta-Reinforcement Learning Agentscited by 1
  24. 2024Black Box Meta-Learning Intrinsic Rewardscited by 1
  25. 2025Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Reviewcited by 1
  26. 2026In-Context Reinforcement Learning under Non-Stationarity: A Surveycited by 1
  27. 2021Behaviour-conditioned policies for cooperative reinforcement learning taskscited by 0
  28. 2022Reusable Options through Gradient-based Meta Learningcited by 0
  29. 2023RL3: Boosting Meta Reinforcement Learning via RL inside RL2cited by 0
  30. 2025Adaptive Policy Backbone via Shared Networkcited by 0
  31. 2025An Information-Theoretic Analysis of OOD Generalization in Meta-Reinforcement Learningcited by 0
  32. 2026Connect the Dots: Training LLMs for Long-Lifecycle Agents with Cross-Domain Generalization Via Reinforcement Learningcited by 0