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Autonomously Reusing Knowledge in Multiagent Reinforcement Learning.

, , and . IJCAI, page 5487-5493. ijcai.org, (2018)

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Transfer Learning for Reinforcement Learning Domains: A Survey, and . Journal of Machine Learning Research, (2009)Multi-objectivization of reinforcement learning problems by reward shaping., , , , , and . IJCNN, page 2315-2322. IEEE, (2014)An Exploration Strategy Facing Non-Stationary Agents., , , , and . AAMAS, page 922-923. ACM, (2017)Speeding up Tabular Reinforcement Learning Using State-Action Similarities., , and . AAMAS, page 1722-1724. ACM, (2017)Transfer via inter-task mappings in policy search reinforcement learning., , and . AAMAS, page 37. IFAAMAS, (2007)Autonomous Extracting a Hierarchical Structure of Tasks in Reinforcement Learning and Multi-task Reinforcement Learning., and . CoRR, (2017)Leveraging human knowledge in tabular reinforcement learning: A study of human subjects., , , and . CoRR, (2018)Is multiagent deep reinforcement learning the answer or the question? A brief survey., , and . CoRR, (2018)When should there be a "Me" in "Team"?: distributed multi-agent optimization under uncertainty., , , , and . AAMAS, page 109-116. IFAAMAS, (2010)Abstraction and Generalization in Reinforcement Learning: A Summary and Framework., , and . ALA, volume 5924 of Lecture Notes in Computer Science, page 1-32. Springer, (2009)