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| Discovery Algorithm for Option Based on Exploration Density |
| MENG JiangHua, ZHU JiHong, SUN ZengQi |
| The State Key Laboratory of Intelligent Technology and System, Department of Computer Science and Technology, Tsinghua University, Beijing 100084 |
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Abstract A new method, named exploration density(ED) inspection, is presented. Useful options were discovered by the method through inspecting the influence of the state on agent’s explore ability in state space. The simulation results show that the proposed algorithm has better performance in reinforcement learning. The method has characteristics of taskindependence, no need of prior knowledge, etc. The created options can be directly shared among different tasks in the same environment.
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Received: 14 March 2006
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(王本年,高 阳,陈兆乾,等.面向Option的K聚类Subgoal发现算法.计算机研究与发展, 2006, 43(5): 851855) |
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2007, Vol. 20 
