A practical guide to multi-objective reinforcement learning and planning von Hayes, Conor F., Rădulescu, Roxana, Bargiacchi, Eugenio, Källström, Johan, Macfarlane, Matthew, Reymond, Mathieu, Verstraeten, Timothy, Zintgraf, Luisa M., Dazeley, Richard, Heintz, Fredrik, Howley, Enda, Irissappane, Athirai A., Mannion, Patrick, Nowé, Ann, Ramos, Gabriel, Restelli, Marcello, Vamplew, Peter, Roijers, Diederik M.

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Coordination of Electric Vehicle Charging Through Multiagent Reinforcement Learning von Silva, Felipe Leno Da, Nishida, Cyntia E. H., Roijers, Diederik M., Costa, Anna H. Reali

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Open-Ended Learning: A Conceptual Framework Based on Representational Redescription von Doncieux, Stephane, Filliat, David, Díaz-Rodríguez, Natalia, Hospedales, Timothy, Duro, Richard, Coninx, Alexandre, Roijers, Diederik M, Girard, Benoît, Perrin, Nicolas, Sigaud, Olivier

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Multi-objective multi-agent decision making: a utility-based analysis and survey von Rădulescu, Roxana, Mannion, Patrick, Roijers, Diederik M., Nowé, Ann

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Actor-critic multi-objective reinforcement learning for non-linear utility functions von Reymond, Mathieu, Hayes, Conor F., Steckelmacher, Denis, Roijers, Diederik M., Nowé, Ann

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A utility-based analysis of equilibria in multi-objective normal-form games von Rădulescu, Roxana, Mannion, Patrick, Zhang, Yijie, Roijers, Diederik M., Nowé, Ann

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Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021) von Vamplew, Peter, Smith, Benjamin J., Källström, Johan, Ramos, Gabriel, Rădulescu, Roxana, Roijers, Diederik M., Hayes, Conor F., Heintz, Fredrik, Mannion, Patrick, Libin, Pieter J. K., Dazeley, Richard, Foale, Cameron

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Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning von Hayes, Conor F., Reymond, Mathieu, Roijers, Diederik M., Howley, Enda, Mannion, Patrick

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On nash equilibria in normal-form games with vectorial payoffs von Röpke, Willem, Roijers, Diederik M., Nowé, Ann, Rădulescu, Roxana

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Opponent learning awareness and modelling in multi-objective normal form games von Rădulescu, Roxana, Verstraeten, Timothy, Zhang, Yijie, Mannion, Patrick, Roijers, Diederik M., Nowé, Ann

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Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighbourhood Structures von Verstraeten, Timothy, Bargiacchi, Eugenio, Libin, Pieter J. K., Helsen, Jan, Roijers, Diederik M., Nowé, Ann

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Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies von Libin, Pieter J. K., Verstraeten, Timothy, Roijers, Diederik M., Grujic, Jelena, Theys, Kristof, Lemey, Philippe, Nowé, Ann

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Efficient Evaluation of Influenza Mitigation Strategies Using Preventive Bandits von Libin, Pieter, Verstraeten, Timothy, Theys, Kristof, Roijers, Diederik M., Vrancx, Peter, Nowé, Ann

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A Survey of Multi-Objective Sequential Decision-Making von Roijers, D. M., Vamplew, P., Whiteson, S., Dazeley, R.

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AI-Toolbox: A C plus plus library for Reinforcement Learning and Planning (with Python Bindings) von Bargiacchi, Eugenio, Roijers, Diederik M., Nowe, Ann

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Time efficiency in optimization with a bayesian-Evolutionary algorithm von Lan, Gongjin, Tomczak, Jakub M., Roijers, Diederik M., Eiben, A.E.

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Learning directed locomotion in modular robots with evolvable morphologies von Lan, Gongjin, De Carlo, Matteo, van Diggelen, Fuda, Tomczak, Jakub M., Roijers, Diederik M., Eiben, A.E.

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Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances von Jiang, Jie, Kong, Qiuqiang, Plumbley, Mark D., Gilbert, Nigel, Hoogendoorn, Mark, Roijers, Diederik M.

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Expected scalarised returns dominance: a new solution concept for multi-objective decision making von Hayes, Conor F., Verstraeten, Timothy, Roijers, Diederik M., Howley, Enda, Mannion, Patrick

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Computing Convex Coverage Sets for Faster Multi-objective Coordination von Roijers, Diederik Marijn, Whiteson, Shimon, Oliehoek, Frans A.

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