Predicting performance in team games: The automatic coach

Abstract

This is an electronic version of the paper presented at the 3rd International Conference on Agents and Artificial Intelligence, held in Rome on 2011A wide range of modern videogames involves a number of players collaborating to obtain a common goal. The way the players are teamed up is usually based on a measure of performance that makes players with a similar level of performance play together. We propose a novel technique based on clustering over observed behaviour in the game that seeks to exploit the particular way of playing of every player to find other players with a gameplay such that in combination will constitute a good team, in a similar way to a human coach. This paper describes the preliminary results using these techniques for the characterization of player and team behaviours. Experiments are performed in the domain of Soccerbots.This work has been partly supported by: Spanish Ministry of Science and Education under grant TIN2009-13692-C03-03, TIN2010-19872 and Spanish Ministry of Industry under grant TSI, 020110- 2009-205