A framework based on evolutionary algorithm for strategy optimization in robot soccer

Author Affiliation

Asma Larik is Visiting Faculty at the Department of Computer Science, Institute of Business Administration (IBA), Karach

Sajjad Haider is Faculty of Computer Science at Institute of Business Administration (IBA), Karachi

Faculty / School

Faculty of Computer Sciences (FCS)

Department

Department of Computer Science

Was this content written or created while at IBA?

Yes

Document Type

Article

Source Publication

Soft Computing

ISSN

1432-7643

Disciplines

Computer Sciences | Geometry and Topology | Mathematics

Abstract

In any competitive and uncertain environment, designing an optimal strategy is a challenging task. The manual hand-coding of strategy is a tedious job, and its evaluation on all possible situations becomes even more complicated. This paper proposes a novel distributed framework, named FEASO, based on evolutionary algorithms, for strategy optimization in the domain of robot soccer. In the context of robot soccer, strategy denotes the critical areas where home team agents should be positioned. The focus of this study is to optimize the strategic placements of agents that are defending the goal. The presented approach comprises three modules: evolutionary algorithm execution, parallel fitness evaluation and fitness computation. It executes matches in parallel on different machines for fitness evaluation. The fitness function takes into account three parameters: the goal difference, regions occupied by defending players and ball possession by the home team players. The framework has been successfully implemented in our 3D soccer simulation team that participates in RoboCup event. Experiments are conducted using binaries of various teams taking part in the competition. A comparison of strategies between teams is conducted and analyzed. The results clearly demonstrate that the team that executes optimized strategy is able to defend more goals as compared to the team with hand-coded strategic points.

Indexing Information

HJRS - W Category, Scopus, Web of Science - Science Citation Index Expanded (SCI)

Publication Status

Published

Link to Full Text

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