Every Team Makes Mistakes, in Large Action Spaces


L. S. Marcolino, V. Nagarajan, and M. Tambe. 2015. “Every Team Makes Mistakes, in Large Action Spaces .” In Multidisciplinary Workshop on Advances in Preference Handling (M-PREF 2015).


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.
See also: 2015