Deep Ordinal Reinforcement Learning

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Weng, P.: Markov decision processes with ordinal rewards: Reference point-based preferences. In: Proceedings of the 21st International Conference on Automated Planning and Scheduling (ICAPS-11). AAAI Press, Freiburg, Germany (2011)

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Weng, P.: Ordinal Decision Models for Markov Decision Processes. In: Proceedings of the 20th European Conference on Artificial Intelligence (ECAI-12). pp. 828–833. IOS Press, Montpellier, France (2012)

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Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., Riedmiller, M.A.: Playing Atari with Deep Reinforcement Learning. CoRR abs/1312.5602

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2013

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Weng, P., Busa-Fekete, R., Hüllermeier, E.: Interactive Q-Learning with Ordinal Rewards and Unreliable Tutor. In: Proceedings of the ECML/PKDD-13 Workshop on Reinforcement Learning from Generalized Feedback: Beyond Numeric Rewards (2013)

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Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A.A., Veness, J., Bellemare, M.G., Graves, A., Riedmiller, M.A., Fidjeland, A., Ostrovski, G., Petersen, S., Beattie, C., Sadik, A., Antonoglou, I., King, H., Kumaran, D., Wierstra, D., Legg, S., Hassabis, D.: Human-level control through deep reinforcement learning. Nature 518

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Gilbert, H., Weng, P.: Quantile reinforcement learning. CoRR abs/1611.00862

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2016

Wirth, C., Akrour, R., Neumann, G., Fürnkranz, J.: A Survey of Preference-Based Reinforcement Learning Methods. Journal of Machine Learning Research 18

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Sutton, R.S., Barto, A.G.: Reinforcement learning - an introduction. Adaptive computation and machine learning, MIT Press, second edn. (2018)

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Joppen, T., Fürnkranz, J.: Ordinal Monte Carlo Tree Search. CoRR abs/1901.04274

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2019

Closest in time.

Zap, A.: Ordinal Reinforcement Learning. Master’s thesis, Technische Universität Darmstadt (2019), To appear

2019

Closest in time.