Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/4204
Title: Fuzzy reinforcement learning and its applications to mobile robot navigation
Authors: Deng, Chang
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Issue Date: 2005
Source: Deng, C. (2005). Fuzzy reinforcement learning and its applications to mobile robot navigation. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: Fuzzy logic is a mathematical approach to emulate the human way of thinking. It has been shown that fuzzy logic could serve as a powerful methodology for dealing with imprecision and nonlinearity efficiently. However, the conventional way of designing a fuzzy system has been a subjective approach. If the fuzzy system somehow possesses learning abilities, an enormous amount of human efforts would be saved from tuning the system.
URI: https://hdl.handle.net/10356/4204
DOI: 10.32657/10356/4204
Rights: Nanyang Technological University
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

Files in This Item:
File Description SizeFormat 
EEE-THESES_262.pdf4.05 MBAdobe PDFThumbnail
View/Open

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.