A Unified Look at Generalization, Transfer Learning and Off-policy Learning
Forthcoming May 2025
References
-
Da Silva, F.L. and Costa, A.H.R., 2019. A survey on transfer learning for multiagent reinforcement learning systems. Journal of Artificial Intelligence Research, 64, pp.645-703.
MR3932559
-
Da Silva, F.L., Glatt, R. and Costa, A.H.R., 2017. Simultaneously learning and advising in multiagent reinforcement learning. Proceedings of the 16th conference on autonomous agents and multiagent systems pp. 1100-1108.
-
Farahmand, A., Ghavamzadeh, M., Szepesvàri, C. and Mannor, S. 2016.
Regularized policy iteration with nonparametric function spaces.
Journal of Machine Learning Research, 17, Paper No. 139, 66 pp.
MR3555030
-
Haarnoja, T., Zhou, A., Abbeel, P. and Levine, S., 2018. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor. Proceedings of the 35th International Conference on Machine Learning, PMLR 80, pp. 1861-1870.
-
Kallus, N. and Uehara, M., 2020. Double reinforcement learning for efficient off-policy evaluation in Markov decision processes.
Journal of Machine Learning Research, Paper No. 167, 63 pp.
MR4209453
-
Kallus, N. and Uehara, M., 2022. Efficiently breaking the curse of horizon in off-policy evaluation with double reinforcement learning, Operations Research 70 no.~6, 3282-3302.
MR4538517
-
Littman, M.L., 2015. Reinforcement learning improves behaviour from evaluative feedback. Nature, 521(7553), pp.445-451.
-
Mohajerin Esfahani, P. and Kuhn, D., 2018.
Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations.
Mathematical Programming 171, no. 1-2, 115-166.
MR3844536
-
Sutton, R. S. and Barto, A.G., 2018. Reinforcement learning: an introduction.. Second edition
Adapt. Comput. Mach. Learn.
MIT Press, Cambridge, MA.
MR3889951
-
Taylor, M.E. and Stone, P., 2009. Transfer learning for reinforcement learning domains: A survey. Journal of Machine Learning Research, 10(7).
MR2534874
-
Teyssière, G., 2025. Review of "Wang, J., Gao, R. and Zha, H., 2024. Reliable off-policy evaluation for reinforcement learning ". Mathematical Reviews, American Mathematical Society.
-
Wang, J., Gao, R., and Zha, H., 2024. Reliable off-policy evaluation for reinforcement learning.
Operation Research, 72, no. 2, 699-716.
MR4677384
-
Yamaguchi, S.Y., Kanai, S., Kumagai, A., Chijiwa, D. and Kashima, H., 2025. Transfer learning with pre-trained conditional generative models. Machine Learning, 114(4), p.96.
MR4867330
-
Zhu, Z., Lin, K., Jain, A.K. and Zhou, J., 2023. Transfer learning in deep reinforcement learning: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(11), pp.13344-13362.
Updated May 2025..