Publications of Simone Parisi

Journal Papers
Parisi, S.; Pirotta, M.; Peters, J. (accepted). Manifold-based Multi-objective Policy Search with Sample Reuse, Neurocomputing.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Parisi, S.; Pirotta, M.; Restelli, M. (2016). Multi-objective Reinforcement Learning through Continuous Pareto Manifold Approximation, Journal of Artificial Intelligence Research (JAIR), 57, pp.187-227.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]
Conference Papers
Tangkaratt, V.; van Hoof, H.; Parisi, S.; Neumann, G.; Peters, J.; Sugiyama, M. (2017). Policy Search with High-Dimensional Context Variables, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Parisi, S; Blank, A; Viernickel T; Peters, J (2016). Local-utopia Policy Selection for Multi-objective Reinforcement Learning, Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Parisi, S.; Abdulsamad, H.; Paraschos, A.; Daniel, C.; Peters, J. (2015). Reinforcement Learning vs Human Programming in Tetherball Robot Games, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Pirotta, M.; Parisi, S.; Restelli, M. (2015). Multi-Objective Reinforcement Learning with Continuous Pareto Frontier Approximation, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Parisi, S.; Pirotta, M.; Smacchia, N.; Bascetta, L.; Restelli, M. (2014). Policy gradient approaches for multi-objective sequential decision making, Proceedings of the International Joint Conference on Neural Networks (IJCNN).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Parisi, S.; Pirotta, M.; Smacchia, N.; Bascetta, L.; Restelli, M. (2014). Policy gradient approaches for multi-objective sequential decision making: A comparison, Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]
Workshop Papers
Simone Parisi, Voot Tangkaratt, Jan Peters (2017). Regularized Contextual Policy Search via Mutual Information, Proceedings of the Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

  

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