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Number of items: 5.

Parisi, S. ; Ramstedt, S. ; Peters, J. (2017):
Goal-Driven Dimensionality Reduction for Reinforcement Learning.
Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), [Conference or Workshop Item]

Parisi, S. ; Pirotta, M. ; Peters, J. (2017):
Manifold-based Multi-objective Policy Search with Sample Reuse.
In: Neurocomputing, 263, pp. 3-14. ISSN 0925-2312,
[Article]

Tangkaratt, V. ; Hoof, H. van ; 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), [Conference or Workshop Item]

Parisi, S. ; Blank, A. ; Viernickel,, T. ; Peters, J. (2016):
Local-utopia Policy Selection for Multi-objective Reinforcement Learning.
In: Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL),
[Conference or Workshop Item]

Parisi, S. ; Abdulsamad, H. ; Paraschos, A. ; Daniel, C. ; Peters, J. (2015):
Reinforcement Learning vs Human Programming in Tetherball Robot Games.
In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS),
[Conference or Workshop Item]

This list was generated on Tue May 24 03:52:24 2022 CEST.