A survey of nature inspired optimization algorithms applied to cooperative strategies in robot soccer

Abstract

Nature inspired optimization algorithms are known for their inherent ability to solve complex problems where multiple agents interact to perform a task at hand. This paper presents a survey of how these optimization algorithms have been applied in determining cooperative strategies for a team of soccer playing agents. The survey discusses the contributions made by researchers and makes an effort to map nature inspired optimization algorithms with the type of cooperative strategy evolved. A categorization of cooperative study is also presented specifically in the domain of RoboCup Soccer Simulation League where agents cooperate in a virtual environment to develop a strategy without any issue of physical wear and tear. This study would serve as a starting point for teams participating in RoboCup competitions to enhance their strategy utilizing ideas from nature inspired algorithms.