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Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning.

P. Vamplew, C. Foale, C. Hayes, P. Mannion, E. Howley, R. Dazeley, S. Johnson, J. Källström, G. de Oliveira Ramos, R. Radulescu, W. Röpke, and D. Roijers. AAMAS, page 2717-2721. ACM, (2024)

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Christina Barbara Petersen

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Rapid Anomaly Detection Using Integrated Prudence Analysis (IPA).O. Maruatona, P. Vamplew, R. Dazeley, and P. Watters. PAKDD (Workshops), volume 11154 of Lecture Notes in Computer Science, page 137-141. Springer, (2018)Human engagement providing evaluative and informative advice for interactive reinforcement learning.A. Bignold, F. Cruz, R. Dazeley, P. Vamplew, and C. Foale. Neural Comput. Appl., 35 (25): 18215-18230 (September 2023)A Prioritized objective actor-critic method for deep reinforcement learning.N. Nguyen, T. Nguyen, P. Vamplew, R. Dazeley, and S. Nahavandi. Neural Comput. Appl., 33 (16): 10335-10349 (2021)Levels of explainable artificial intelligence for human-aligned conversational explanations.R. Dazeley, P. Vamplew, C. Foale, C. Young, S. Aryal, and F. Cruz. CoRR, (2021)Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021).P. Vamplew, B. Smith, J. Källström, G. de Oliveira Ramos, R. Radulescu, D. Roijers, C. Hayes, F. Heintz, P. Mannion, P. Libin and 2 other author(s). CoRR, (2021)More Effective Web Search Using Bigrams and Trigrams.D. Johnson, V. Malhotra, and P. Vamplew. Webology, (2006)Portal-based sound propagation for first-person computer games.C. Foale, and P. Vamplew. IE, volume 305 of ACM International Conference Proceeding Series, page 9. ACM, (2007)Incorporating Expert Advice into Reinforcement Learning Using Constructive Neural Networks.R. Ollington, P. Vamplew, and J. Swanson. Constructive Neural Networks, volume 258 of Studies in Computational Intelligence, Springer, (2009)Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios.F. Cruz, C. Young, R. Dazeley, and P. Vamplew. IROS, page 894-901. IEEE, (2022)The Combative Accretion Model - Multiobjective Optimisation Without Explicit Pareto Ranking.A. Berry, and P. Vamplew. EMO, volume 3410 of Lecture Notes in Computer Science, page 77-91. Springer, (2005)

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Disambiguation of "Vamplew, Peter"

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Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning.

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Tanja Elisabeth Peters

Andre Peters

Jillian Petersen

Robert Martin Peterreins

Christina Barbara Petersen

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Disambiguation of "Vamplew, Peter"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning.

Please choose a person to relate this publication to

Tanja Elisabeth Peters

Andre Peters

Jillian Petersen

Robert Martin Peterreins

Christina Barbara Petersen

Other publications of authors with the same name

Disambiguation

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URL
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Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning.