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Results: 5
Number of items: 5
  • Open Access
    Snel, M. (2018). Generalization strategies in reinforcement learning. [Thesis, externally prepared, Universiteit van Amsterdam].
  • Open Access
    Snel, M., & Whiteson, S. (2014). Learning Potential Functions and their Representations for Multi-Task Reinforcement Learning. Autonomous Agents and Multi-Agent Systems, 28(4), 637-681. https://doi.org/10.1007/s10458-013-9235-z
  • Open Access
    Snel, M., & Whiteson, S. (2012). Multi-task reinforcement learning: shaping and feature selection. In S. Sanner, & M. Hutter (Eds.), Recent Advances in Reinforcement Learning: 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011 : revised selected papers (pp. 237-248). (Lecture Notes in Computer Science; Vol. 7188), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-642-29946-9_24
  • Snel, M., Whiteson, S., & Kuniyoshi, Y. (2011). Robust central pattern generators for embodied hierarchical reinforcement learning. In 2011 IEEE International Conference on Development and Learning (ICDL) (pp. 1-6). IEEE. https://doi.org/10.1109/DEVLRN.2011.6037352
  • Snel, M., & Whiteson, S. (2010). Multi-task evolutionary shaping without pre-specified representations. In J. Branke (Ed.), GECCO 2010: Proceedings of the Genetic and Evolutionary Computation Conference (pp. 1031-1038). ACM. http://doi.acm.org/10.1145/1830483.1830671
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