No abstract

No abstract

Abstract. This work proposes a novel approach for introducing market-driven strategy to robot soccer domain in order to solve vital issues related to multiagent coordination. In robot soccer, two teams of robots compete with each other to win the match. For the benefit of the team, the robots should work collaboratively, whenever possible. Market-driven approach applies the basic properties of free market economy to a team of robots, to increase the profit of team as much as possible. This approach is based on the assumption that maximizing individual profit will approximate global profit maximization. In several works, this method was applied to some open issues in multi-agent systems like multi-robot exploration and coordination, but these implementations were limited. In this work, this approach is applied for the first time to the robot soccer domain, which is being a complex, dynamic and real-time event, one of the prominent topics of multi-agent research. In this paper, a market-driven collaborative task allocation algorithm for the robot soccer domain is proposed and experimental results are discussed.

No abstract

No abstract