Abstract:

Q-learning algorithm can study without prior knowledge, and it is good at solving complicated optimal decision problems in many fields. by analyzing the popular algorithms for air combat target assignment, a Q-learning algorithm is proposed for solving it in agent-based modeling and simulation (ABMS). Firstly, modeling of this problem is introduced in the attributions, structure and action rules. Then, the flowchart of the Q-learning algorithm is given out. Furthermore, the criteria of state-action-pair are well defined. Finally, the simulation results show that the method is reasonable and valid. The method can avoid relying on the prior knowledge and get out of the local optimal solution.