Using model-based collaborative filtering techniques to recommend the expected best strategy to defeat a simulated soccer opponent

• Type: Article in International Scientific Journal
• Date: 2014

Authors

Pedro Henriques Abreu (Author) Other; Daniel Castro Silva (Author) FEUP; João Portela (Author) FEUP; João Mendes-Moreira (Author) FEUP; Luis Paulo Reis (Author) Other

Journal

Title: Intelligent Data Analysis

Vol. 18 No. 5

Pages: 973-991

ISSN: 1088-467X

Publisher: IOS PRESS

Indexing

ISI Web of Knowledge - 6 Citations

ISI Web of Science

Scopus

COMPENDEX

INSPEC

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Physical sciences > Computer science > Cybernetics > Artificial intelligence

Other information

Authenticus ID: P-009-W4B

DOI: 10.3233/ida-140678

Abstract (EN): How to improve the performance of a simulated soccer team using final game statistics? This is the question this research aims to answer using model-based collaborative techniques and a robotic team - FC Portugal - as a case study. After developing a framework capable of automatically calculating the final game statistics through the RoboCup log files, a feature selection algorithm was used to select the variables that most influence the final game result. In the next stage, given the statistics of the current game, we rank the strategies that obtained the maximum average of goal difference in similar past games. This is done by splitting offline past games into different k-clusters. Then, for each cluster, the expected best strategy was assigned. The online phase consists in the selection of the expected best strategy for the cluster in which the current game best fits. Regarding the final results, our approach proved that it is possible to improve the performance of a robotic team by more than 35%, even in a competitive environment such as the RoboCup 2D simulation league.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 19