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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)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)Transfer Learning for Reinforcement Learning Domains: A Survey, and . Journal of Machine Learning Research, (2009)Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines., , , , , and . ECML/PKDD (2), volume 8189 of Lecture Notes in Computer Science, page 449-464. Springer, (2013)AI Projects for Computer Science Capstone Classes (Extended Abstract)., and . AAAI, page 4819-4821. AAAI Press, (2017)Scalable Multitask Policy Gradient Reinforcement Learning., , and . AAAI, page 1847-1853. AAAI Press, (2017)