Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 89
Number of items: 89
  • Open Access
    Roijers, D. M., Vamplew, P., Whiteson, S., & Dazeley, R. (2013). A Survey of Multi-Objective Sequential Decision-Making. Journal of Artificial Intelligence Research, 48, 67-113. https://doi.org/10.1613/jair.3987
  • Open Access
    Hofmann, K., Schuth, A., Whiteson, S., & de Rijke, M. (2013). Reusing Historical Interaction Data for Faster Online Learning to Rank for IR. In WSDM 2013: proceedings of the 6th ACM International Conference on Web Search and Data Mining: February 4-8, 2013, Rome, Italy (pp. 183-192). ACM. https://doi.org/10.1145/2433396.2433419
  • Open Access
    Hofmann, K. (2013). Fast and reliable online learning to rank for information retrieval. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Oliehoek, F. A., Spaan, M. T. J., Amato, C., & Whiteson, S. (2013). Incremental Clustering and Expansion for Faster Optimal Planning in Decentralized POMDPs. Journal of Artificial Intelligence Research, 46, 449-509. https://doi.org/10.1613/jair.3804
  • Open Access
    Li, G., Hung, H., Whiteson, S., & Knox, W. B. (2013). Using informative behavior to increase engagement in the TAMER framework. In AAMAS'13: proceedings of the 2013 International Conference on Autonomous Agents & Multiagent Systems : May 6-10, 2013, St. Paul, MN, USA (Vol. 2, pp. 909-916). International Foundation for Autonomous Agents and Multiagent Systems. http://dl.acm.org/citation.cfm?id=2485064
  • Oliehoek, F. A., Whiteson, S., & Spaan, M. T. J. (2012). Exploiting structure in cooperative Bayesian games. In N. de Freitas, & K. Murphy (Eds.), Uncertainty in Artificial: proceedings of the Twenty-Eight conference (2012): August 15-17, 2012 Catalina Island, CA (pp. 654-664). AUAI Press. http://www.auai.org/uai2012/proceedings.pdf
  • 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
  • Rao, K., & Whiteson, S. (2012). V-MAX: tempered optimism for better PAC reinforcement learning. In AAMAS 2012: Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multi-Agent Systems (pp. 375-382). AAMAS.
  • Whiteson, S. (2012). Evolutionary computation for reinforcement learning. In M. Wiering, & M. van Otterlo (Eds.), Reinforcement learning: state-of-the-art (pp. 325-358). (Adaptation, learning, and optimization; No. 12). Springer. https://doi.org/10.1007/978-3-642-27645-3_10
  • Hofmann, K., Whiteson, S., & de Rijke, M. (2012). Estimating interleaved comparison outcomes from historical click data. In CIKM’12: the proceedings of the 21st ACM International Conference on Information and Knowledge Management : October 29–November 2, 2012 Maui, Hawaii, USA (pp. 1779-1783). Association for Computing Machinery. https://doi.org/10.1145/2396761.2398516
Page 6 of 9