Abstract
We systematically explore a range of variations of our TAC travelshopping agent, Walverine. The space of strategies is defined by settings to behavioral parameter values. Our empirical game-theoretic analysis is facilitated by approximating games through hierarchical reduction methods. This approach generated a small set of candidates for the version to run in the TAC-05 tournament. We selected among these based on performance in preliminary rounds, ultimately identifying a successful strategy for Walverine 2005. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Wellman, M. P., Reeves, D. M., Lochner, K. M., & Suri, R. (2006). Searching for Walverine 2005. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3937 LNAI, pp. 157–170). Springer Verlag. https://doi.org/10.1007/11888727_12
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