An Architecture of Intelligent Multi-Agent System: a Case Study in Soccergame Simulation

Abstract

Multi-agent collaboration or teamwork and learning are critical research challenges especially for a large number of multi-agent applications. In multi-agent system, agents must accurately perceive and act despite a quickly changing and noisy environment. They have to act not only at individual skills but also at collaborative and adversarial behaviours. Soccer team simulations are used to provide a suitable test bed for research in multi-agent collaboration systems. In this paper, we proposed agent architecture for soccer team simulation. It is an agent architecture within which a flexible team organization and decision-making are presented. The proposed agent architecture includes four main components. First, the world model that describes the environment, which provides a very important resource for making decisions. The world model information is collected through environment monitoring and world prediction for the unobserved information. The second component is team organization, which is achieved by means of “Team Agreement”. The third one is an inter-agent communication paradigm that enables team coordination and knowledge transfer between agents. The fourth is a decision-making process, which includes passing policy, shoots policy, and strategic position policy. In the decision-making process, we proposed and implemented heuristic passing algorithm, neural-network-based shooting algorithm, and heuristic strategic position algorithm. Experimental results of the proposed system prove its stability and applicability. Hence more, the experimental results conclude that coaching enhances the proposed collaboration multi-agent system.