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Results: 89
Number of items: 89
  • 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
  • van den Berg, T., & Whiteson, S. (2013). Critical Factors in the Performance of HyperNEAT. In C. Blum (Ed.), GECCO'13: proceedings of the 2013 Genetic and Evolutionary Computation Conference: July 6-10, 2013, Amsterdam, The Netherlands (pp. 759-766). ACM. https://doi.org/10.1145/2463372.2463460
  • Hofmann, K., Whiteson, S., & de Rijke, M. (2013). Fidelity, Soundness, and Efficiency of Interleaved Comparison Methods. ACM Transactions on Information Systems, 31(4), Article 17. https://doi.org/10.1145/2536736.2536737
  • 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
  • Schuth, A., Hofmann, K., Whiteson, S., & de Rijke, M. (2013). Lerot: An Online Learning to Rank Framework. In LivingLab'13: Proceedings of the 2013 workshop on Living labs for information retrieval evaluation (pp. 23-26). ACM. https://doi.org/10.1145/2513150.2513162
  • 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
    Roijers, D. M., Whiteson, S., & Oliehoek, F. A. (2013). Computing Convex Coverage Sets for Multi-Objective Coordination Graphs. In P. Perny, M. Pirlot, & A. Tsoukiàs (Eds.), Algorithmic Decision Theory: Third International Conference, ADT 2013, Bruxelles, Belgium, November 12-14, 2013 : proceedings (pp. 309-323). (Lecture Notes in Computer Science; Vol. 8176), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-642-41575-3_24
  • 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
  • Open Access
    Hofmann, K., Whiteson, S., & de Rijke, M. (2013). Balancing Exploration and Exploitation in Listwise and Pairwise Online Learning to Rank for Information Retrieval. Information Retrieval, 16(1), 63-90. https://doi.org/10.1007/s10791-012-9197-9
  • Open Access
    Hofmann, K. (2013). Fast and reliable online learning to rank for information retrieval. [Thesis, fully internal, Universiteit van Amsterdam].
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