Every team makes mistakes, in large action spaces

Soriano Marcolino, Leandro and Nagarajan, Vaishnavh and Tambe, Milind (2015) Every team makes mistakes, in large action spaces. In: 9th Multidisciplinary Workshop on Advances in Preference Handling (M-PREF 2015) :. UNSPECIFIED.

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Voting is applied to better estimate an optimal answer to complex problems in many domains. We recently presented a novel benefit of voting, that has not been observed before: we can use the voting patterns to assess the performance of a team and predict whether it will be successful or not in problem-solving. Our prediction technique is completely domain independent, and it can be executed at any time during problem solving. In this paper we present a novel result about our technique: we show that the prediction quality increases with the size of the action space. We present a theoretical explanation for such phenomenon, and experiments in Computer Go with a variety of board sizes.

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19 Sep 2016 09:54
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27 Apr 2024 00:46