贴图编码在强化学习中的性能评价

Kenji Ota, T. Ozeki
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引用次数: 1

摘要

强化学习是人工智能的研究领域之一。在计算机模拟中,学习方法通常假定为离散状态。然而,我们必须在现实情况下对待连续值。本文研究了具有代表性的连续状态处理技术瓦片编码方案的各种技术。在空间搜索问题上,对单次平铺法、多次平铺法、时移法和所提方法的性能进行了检验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Evaluation of Tile Coding in Reinforcement Learning
Reinforcement learning is one of research fields in artificial intelligence. The learning method usually assumes a discrete state in computer simulations. However, we must treat a continuous value in a realistic situation. In this paper, we investigate various techniques of the tile cording scheme which is a representative technique to handle continuous states. We check the performance of single tiling, multiple tiling, time-shift method and the proposed method in the issue of space search.
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