Mining Balanced Sequential Patterns in RTS Games 1Reportar como inadecuado

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1 DM2L - Data Mining and Machine Learning LIRIS - Laboratoire d-InfoRmatique en Image et Systèmes d-information 2 ORPAILLEUR - Knowledge representation, reasonning Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery 3 GameLab MIT MIT - Massachusetts Institute of Technology

Abstract : The video game industry has grown enormously over the last twenty years, bringing new challenges to the artificial intelli-gence and data analysis communities. We tackle here the problem of automatic discovery of strategies in real-time strategy games through pattern mining. Such patterns are the basic units for many tasks such as automated agent design, but also to build tools for the profession-ally played video games in the electronic sports scene. Our formal-ization relies on a sequential pattern mining approach and a novel measure, the balance measure, telling how a strategy is likely to win. We experiment our methodology on a real-time strategy game that is professionally played in the electronic sport community.

Autor: Guillaume Bosc - Mehdi Kaytoue - Chedy Raïssi - Jean-François Boulicaut - Philip Tan -



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