基于模糊强度的XCS:在多步骤环境问题中的应用

P. Srinil, P. Thongnim, S. Foitong, O. Pinngern
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摘要

本文提出了一种在线模糊系统构建算法,称为FsXCS (fuzzy Strength-Based XCS)。FsXCS是将XCS与模糊逻辑理论相结合,解决多步连续输入输出问题的扩展XCS系统。实际上,从规则泛化系统的角度考虑,XCS是一个非常关注的离散值系统。然而,当扩展到连续值系统时,它变得更加困难,当处理多步连续输入输出问题时,它变得更加困难。为了开发FsXCS,我们在不影响原XCS学习过程的前提下,对XCS的一些组件提出了新的计算细节。在经典连续仿真问题上测试了FsXCS的性能;n环境,自动倒车。实验结果与高离散化的表格q - learning进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy strength-based XCS: An application on multi-step environment problems
This paper proposes an algorithm to perform an online fuzzy system construction was called FsXCS (Fuzzy Strength-Based XCS). FsXCS is the extended XCS system combining XCS with fuzzy logic theory to tackle the multi-step continuous input-output problems. Indeed, XCS is a great attention discrete-valued system considering from the rule generalization system. However, it becomes more difficult when extending to continuous-valued systems, and even more difficult when addressed in multi-step continuous input-output problems. In order to develop FsXCS, we propose new computation details on some XCS components while these changes do not affect the original XCS's learning procedures. The performance of FsXCS was tested on simulation classical continuous problems; n-Environment, and automatically back driving a truck. The experimental results ware compared to the tabular Q-Learing with high discretization.
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