Efficient Exploration With Latent Structure

Bethany R. Leffler, M. Littman, Alexander L. Strehl, Thomas J. Walsh
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引用次数: 13

Abstract

When interacting with a new environment, a robot can improve its online performance by efficiently exploring the effects of its actions. The efficiency of exploration can be expanded significantly by modeling and using latent structure to generalize experiences. We provide a theoretical development of the problem of exploration with latent structure, analyze several algorithms and prove matching lower bounds. We demonstrate our algorithmic ideas on a simple robot car repeatedly traversing a path with two different surface properties.
利用潜在结构进行高效勘探
当与新环境交互时,机器人可以通过有效地探索其动作的效果来提高其在线性能。通过建模和利用潜在结构来推广经验,可以显著提高勘探效率。我们提供了潜在结构探索问题的理论发展,分析了几种算法并证明了匹配下界。我们在一个简单的机器人汽车上演示了我们的算法思想,该机器人汽车反复穿越具有两种不同表面特性的路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
12.00
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0.00%
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