Cooperative learning-agents for task allocation problem

Abstract

In this paper, we will present a working methodology for solving the task allocation problem in a multi-robot system, i.e. assign the tasks being performed to appropriate robots. In fact, the proposed approach combines the advantages of several well-known algorithms (e.g. quantum genetic algorithms, Q-learning machine-learning, etc.), in order to construct a good solution for the task allocation problem. Besides, the proposed working methodology has been implemented using the Java programming language and the JADE multi-agent platform; also it has been simulated on a real-life scenario, which is the extinction of fires (tasks) in an environment altered by a natural disaster. Finally, the experimental results are promising and show the effectiveness of the proposed methodology.