Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 9
Number of items: 9
  • van Seijen, H., Whiteson, S., & Kester, L. (2014). Efficient Abstraction Selection in Reinforcement Learning. Computational Intelligence, 30(4), 657-699. https://doi.org/10.1111/coin.12016
  • van Seijen, H., Whiteson, S., & Kester, L. (2013). Efficient Abstraction Selection in Reinforcement Learning. In A. M. Frisch, & P. Gregory (Eds.), Proceedings, The Tenth Symposium on Abstraction, Reformulation, and Approximation (SARA 2013) (pp. 123-127). AAAI Press. http://www.aaai.org/ocs/index.php/SARA/SARA13/paper/view/7259/6271
  • Open Access
    van Seijen, H., Whiteson, S., van Hasselt, H., & Wiering, M. (2011). Exploiting best-match equations for efficient reinforcement learning. Journal of Machine Learning Research, 12, 2045-2094. http://jmlr.csail.mit.edu/papers/v12/vanseijen11a.html
  • Open Access
    van Seijen, H. H. (2011). Reinforcement learning under space and time constraints. [Thesis, fully internal, Universiteit van Amsterdam].
  • van Seijen, H., Whiteson, S., & Kester, L. (2010). Switching between representations in reinforcement learning. In R. Babuška, & F. C. A. Groen (Eds.), Interactive collaborative information systems (pp. 65-84). (Studies in computational intelligence; No. 281). Springer. https://doi.org/10.1007/978-3-642-11688-9_3
  • van Seijen, H., & Whiteson, S. (2009). Postponed updates for temporal-difference reinforcement learning. In 2009 9th International Conference on Intelligent Systems Design and Applications (ISDA 2009): Pisa, Italy, 30 November-2 December 2009 (pp. 665-672). IEEE. http://doi.ieeecomputersociety.org/10.1109/ISDA.2009.76
  • van Seijen, H., van Hasselt, H., Whiteson, S., & Wiering, M. (2009). A theoretical and empirical analysis of Expected Sarsa. In Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (pp. 177-184). IEEE. https://doi.org/10.1109/ADPRL.2009.4927542
  • van Seijen, H., Bakker, B., & Kester, L. (2008). Switching between different state representations in reinforcement learning. In A. Gammerman (Ed.), Proceedings of the IASTED International Conference on Artificial Intelligence and Applications: As part of the 26th IASTED International Multi-Conference on Applied Informatics, February 11-13, 2008, Innsbruck, Austria (pp. 595-163). ACTA. http://www.actapress.com/Abstract.aspx?paperId=32307
  • van Seijen, H. H., Bakker, B., & Kester, L. J. H. M. (2007). Reinforcement Learning with Multiple, Qualitatively Different State Representations. In Proceedings of NIPS 2007 Workshop on Hierarchical Organization of Behavior
Page of