mlsanityData to 7 Oct 2026

A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning

arXiv 1902.00843 ↗First posted 3 Feb 2019cs.LG stat.MLcited by 18

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Abstract (arXiv)

In this paper we consider the problem of how a reinforcement learning agent that is tasked with solving a sequence of reinforcement learning problems (a sequence of Markov decision processes) can use knowledge acquired early in its lifetime to improve its ability to solve new problems. We argue that previous experience with similar problems can provide an agent with information about how it should explore when facing a new but related problem. We show that the search for an optimal exploration strategy can be formulated as a reinforcement learning problem itself and demonstrate that such strategy can leverage patterns found in the structure of related problems. We conclude with experiments that show the benefits of optimizing an exploration strategy using our proposed approach.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Feb 2019.

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Citing papers per year: 2021: 6; 2022: 6; 2023: 2; 2024: 1; 2025: 3.

18 papers.

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  1. 2023Human-Timescale Adaptation in an Open-Ended Task Spacecited by 136
  2. 2021A Survey of Exploration Methods in Reinforcement Learningcited by 68
  3. 2022How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Compositioncited by 27
  4. 2021Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Surveycited by 23
  5. 2021Provably Efficient Multi-Task Reinforcement Learning with Model Transfercited by 16
  6. 2025A Survey of Continual Reinforcement Learningcited by 16
  7. 2021Learning an Explicit Hyperparameter Prediction Function Conditioned on Taskscited by 9
  8. 2022Automated Reinforcement Learning: An Overviewcited by 9
  9. 2022Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learningcited by 9
  10. 2024A Survey Analyzing Generalization in Deep Reinforcement Learningcited by 8
  11. 2025Continual Reinforcement Learning by Planning with Online World Modelscited by 8
  12. 2022Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation Approachcited by 6
6 more
  1. 2021Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machinescited by 5
  2. 2021Behavior Self-Organization Supports Task Inference for Continual Robot Learningcited by 4
  3. 2025MOORL: A Framework for Integrating Offline-Online Reinforcement Learningcited by 4
  4. 2022Reinforcement Teachingcited by 1
  5. 2022Knowing the Past to Predict the Future: Reinforcement Virtual Learningcited by 0
  6. 2023Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processescited by 0