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It is difficult to automatically discovering hierarchies in multi-agent reinforcement learning. We consider an immune clustering approach for automatically discovering hierarchies in option learning framework. The leading agent generates an undirected edge-weighted topological graph of the environment state transitions based on the environment information explored by all agents. An immune clustering...
MAXQ is a new framework for multi-agent reinforcement learning. But the MAXQ framework cannot decompose all subtasks into more refined hierarchies and the hierarchies are difficult to be discovered automatically. In this paper, a multi-agent hierarchical reinforcement learning approach, named OptMAXQ, by integrating Options into MAXQ is presented. In the OptMAXQ framework, the MAXQ framework is used...
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