Dynamic agent-based reward shaping for multi-agent systems

Earlier works have reported that reward shaping accelerates the convergence of reinforcement learning algorithms. It also helps to make better use of existing information. In this article we propose the use to modify Q-learning in multiagent systems by the use of reward shaping depending on agent state regarding other agents. We study this method with… (More)