TitleExploiting early intent recognition for competitive advantage
Publication TypeConference Paper
Year of Publication2009
AuthorsLaviers, K, Sukthankar, G, Molineaux, M, Aha, DW
Conference NameIJCAI Workshop on Plan, Activity, and Intent Recognition
PublisherAAAI Press
Conference LocationPasadena, CA
Keywordsgame AI, Opponent modeling, plan recognition
Abstract

In physical domains (military or athletic), team behaviors often have an observable spatio-temporal structure, defined by the relative physical positions of team members over time. In this paper, we demonstrate that this structure can be exploited to recognize football plays in the Rush 2008 football simulator. Although events in the simulator are stochastically generated, we present a method for reliably recognizing football plays at a very early stage using multiple support vector machines; moreover, we demonstrate that having this early information about the defense’s intent can be utilized to improve offensive team play. Our system evaluates the competitive advantage of executing a play switch based on the potential of other plays to improve the yardage scored and the similarity of the candidate plays to the current play. Our play switch selection mechanism outperforms both the basic offense and a greedy yardage-based switching strategy.

Refereed DesignationRefereed
Full Text
pdf: 
http://www.nrl.navy.mil/itd/aic/sites/www.nrl.navy.mil.itd.aic/files/pdfs/pair2009-rush.pdf
NRL Publication Release Number: 
09-1226-0949
pub_tags: 
opponent modeling
game AI
plan recognition
key_pub_tags: