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Neurocomputing, Volume 263

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Volume 263, November 2017

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Madalina M. Drugan, Marco A. Wiering, Peter Vamplew, Madhu Chetty:
Special issue on multi-objective reinforcement learning. 1-2

Reinforcement learning algorithms for learning tasks with multiple conflicting objectives

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Simone Parisi, Matteo Pirotta, Jan Peters:
Manifold-based multi-objective policy search with sample reuse. 3-14
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  - journals/ijon/Ruiz-MontielMP17
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Manuela Ruiz-Montiel, Lawrence Mandow, José-Luis Pérez-de-la-Cruz:
A temporal difference method for multi-objective reinforcement learning. 15-25
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Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale, Adam Berry, Tim Moore, Douglas C. Creighton:
Steering approaches to Pareto-optimal multiobjective reinforcement learning. 26-38

Incorporating additional objectives into existing reinforcement learning tasks

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  - journals/ijon/KarimpanalW17
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Thommen George Karimpanal, Erik Wilhelm:
Identification and off-policy learning of multiple objectives using adaptive clustering. 39-47
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Tim Brys, Anna Harutyunyan, Peter Vrancx, Ann Nowé, Matthew E. Taylor:
Multi-objectivization and ensembles of shapings in reinforcement learning. 48-59

Single-objective reinforcement learning methods in the context of multiobjective reinforcement learning

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  - journals/ijon/MannionDMDH17
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Patrick Mannion, Sam Devlin, Karl Mason, Jim Duggan, Enda Howley:
Policy invariance under reward transformations for multi-objective reinforcement learning. 60-73
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Peter Vamplew, Richard Dazeley, Cameron Foale:
Softmax exploration strategies for multiobjective reinforcement learning. 74-86

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