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Recursive channel selection techniques for brain computer interfaces., , и . EMBC, стр. 1753-1756. IEEE, (2012)Feature Reinforcement Learning using Looping Suffix Trees., , и . EWRL, том 24 из JMLR Proceedings, стр. 11-24. JMLR.org, (2012)Q-learning for history-based reinforcement learning., , и . ACML, том 29 из JMLR Workshop and Conference Proceedings, стр. 213-228. JMLR.org, (2013)Learning Agents with Evolving Hypothesis Classes., и . AGI, том 7999 из Lecture Notes in Computer Science, стр. 150-159. Springer, (2013)Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition., , , , и . AAMAS, стр. 2827-2829. ACM, (2023)Optimistic Agents Are Asymptotically Optimal., и . Australasian Conference on Artificial Intelligence, том 7691 из Lecture Notes in Computer Science, стр. 15-26. Springer, (2012)Feature Reinforcement Learning in Practice., , и . EWRL, том 7188 из Lecture Notes in Computer Science, стр. 66-77. Springer, (2011)Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems., , , , , , , , и . ALIFE, стр. 103-110. MIT Press, (2019)Coding of Non-Stationary Sources as a Foundation for Detecting Change Points and Outliers in Binary Time-Series., , и . AusDM, том 134 из CRPIT, стр. 79-84. Australian Computer Society, (2012)Reinforcement Learning in Large Discrete Action Spaces., , , и . CoRR, (2015)