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Results: 89
Number of items: 89
  • Schuth, A., Sietsma, F., Whiteson, S., & de Rijke, M. (2014). Optimizing Base Rankers Using Clicks: A Case Study using BM25. In M. de Rijke, T. Kenter, A. P. de Vries, C. X. Zhai, F. de Jong, K. Radinsky, & K. Hofmann (Eds.), Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014: proceedings (pp. 75-87). (Lecture Notes in Computer Science; Vol. 8416). Springer. https://doi.org/10.1007/978-3-319-06028-6_7
  • Open Access
    Satsangi, Y., Whiteson, S., & Oliehoek, F. A. (2014). Exploiting Submodular Value Functions for Faster Dynamic Sensor Selection: Extended Version. (IAS technical reports; No. IAS-UVA-14-02). University of Amsterdam.
  • Open Access
    Bakkes, S., & Whiteson, S. (2014). Towards Challenge Balancing for Personalised Game Spaces. In Proceedings of Workshops Colocated with the 9th International Conference on the Foundations of Digital Games Society for the Advancement of the Science of Digital Games. http://www.fdg2014.org/workshops/pcg2014_paper_01.pdf
  • Open Access
    Li, G., Hung, H., Whiteson, S., & Knox, W. B. (2014). Learning from Human Reward Benefits from Socio-competitive Feedback. In IEEE ICDL-EPIROB 2014: the Fourth Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics: October 13-16, 2014, Palazzo Ducale, Genoa, Italy (pp. 93-100). IEEE. https://doi.org/10.1109/DEVLRN.2014.6982960
  • Open Access
    Roijers, D. M., Scharpff, J., Spaan, M. T. J., Oliehoek, F. A., De Weerdt, M. M., & Whiteson, S. (2014). Bounded Approximations for Linear Multi-Objective Planning under Uncertainty. BNAIC, 26, 168-169. http://www.cs.kuleuven.be/~joost/DN/bnaic-proceedings/bnaic2014.pdf
  • Open Access
    Zoghi, M., Whiteson, S., Munos, R., & de Rijke, M. (2014). Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem. JMLR Workshop and Conference Proceedings, 32, 10-18. http://jmlr.org/proceedings/papers/v32/zoghi14.html
  • Open Access
    Inja, M., Kooijman, C., de Waard, M., Roijers, D. M., & Whiteson, S. (2014). Queued Pareto Local Search for Multi-Objective Optimization. In T. Bartz-Beielstein, J. Branke, B. Filipič, & J. Smith (Eds.), Parallel Problem Solving from Nature – PPSN XIII: 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014: proceedings (pp. 589-599). (Lecture Notes in Computer Science; Vol. 8672). Springer. https://doi.org/10.1007/978-3-319-10762-2_58
  • 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
    Bakkes, S., & Whiteson, S. (2014). Design Criteria for Challenge Balancing of Personalised Game Spaces. In T. Barnes, & I. Bogost (Eds.), Proceedings of the 9th International Conference on the Foundations of Digital Games Society for the Advancement of the Science of Digital Games. http://www.fdg2014.org/papers/fdg2014_poster_02.pdf
  • Open Access
    Bakkes, S., Whiteson, S., Li, G., Vişniuc, G. V., Charitos, E., Heijne, N., & Swellengrebel, A. (2014). Challenge Balancing for Personalised Game Spaces. In 2014 IEEE Games Media Entertainment (GEM): 22-24 Oct. 2014 (pp. 10). IEEE. https://doi.org/10.1109/GEM.2014.7047971
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