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We consider the problem of knowledge transfer when an agent is facing a series of Reinforcement Learning (RL) tasks.
X—outline of a Theory of Statistical Estimation Based on the Classical Theory of Probability
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Optimal Transport: Old and New , volume 338
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Transfer Learning for Reinforcement Learning Domains: A Survey
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Rao, K.; and Whiteson, S. 2012 · 2012
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Puterman, M. L. 2014 · 2014
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Policy gradient in Lipschitz Markov Decision Processes
Pirotta, M.; Restelli, M.; and Bascetta, L. 2015 · 2015
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Improving PAC Exploration using the Median of Means
Pazis, J.; Parr, R. E.; and How, J. P. 2016 · 2016
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Measuring the Distance Between Finite Markov Decision Processes
Song, J.; Gao, Y.; Wang, H.; and An, B. 2016 · 2016
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Dann, C.; Lattimore, T.; and Brunskill, E. 2017 · 2017
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Sample Complexity of Multi-task Reinforcement Learning
Brunskill, E.; and Li, L. 2013 · 2013
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Clustering Markov Decision Processes for Continual Transfer
Mahmud, M. M.; Hawasly, M.; Rosman, B.; and Ramamoorthy, S. 2013 · 2013
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Lifelong Machine Learning Systems: Beyond Learning Algorithms
Silver, D. L.; Yang, Q.; and Li, L. 2013 · 2013
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An Automated Measure of MDP Similarity for Transfer in Reinforcement Learning
Ammar, H. B.; Eaton, E.; Taylor, M. E.; Mocanu, D. C.; Driessens, K.; Weiss, G.; and Tuyls, K. 2014 · 2014
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Policy and Value Transfer in Lifelong Reinforcement Learning
Abel, D.; Jinnai, Y.; Guo, S. Y.; Konidaris, G.; and Littman, M. L. 2018 · 2018
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Lipschitz Continuity in Model-Based Reinforcement Learning
Asadi, K.; Misra, D.; and Littman, M. L. 2018 · 2018
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Sutton, R. S.; and Barto, A. G. 2018 · 2018
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