Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science submitted time 2022-10-26 Cooperative journals: 《桂林电子科技大学学报》
Abstract： To solve the problem that agents cannot make effective decisions under local observation, a conflict resolution
method combined with deep reinforcement learning is proposed. Based on DDQN algorithm, this method uses the characteristics
of reinforcement learning mode to calculate the cumulative return of agent and determine the priority of agent through
the return value, so as to achieve the purpose of conflict resolution. The method is evaluated by simulating the traffic jam in
real life, and the experimental results show that the method can effectively solve the agent conflict.
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