Abstract: We report on experiments designed to highlight the strengths and weaknesses of an autonomous rule acquisition algorithm for the fuzzy controller ...
strengths and weaknesses of an autonomous rule acquisition algorithm for the fuzzy controller of a simulated mobile robot.
Anthony G. Pipe, Brian Carse, E. Malliris: Experiments on a Pittsburgh-style fuzzy classifier system for mobile robotics. ISIC 2002: 61-66.
New work carried out in simulation on a performance comparison between the Michigan and Pittsburgh Fuzzy Classifier System approaches to a control problem ...
We present a Michigan-style Fuzzy Classifier System architecture, which operates at the level of individual rules. We compare performance of this ...
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"Michigan" and "Pittsburgh" Fuzzy Classifier Systems for Learning. Mobile Robot Control Rules: an Experimental Comparison. Anthony G. Pipe and Brian Carse.
This paper presents new work on a performance comparison between the Michigan [7] and Pittsburgh [1] [5] Fuzzy Classifier System approaches to a problem in ...
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Fuzzy classifier system architectures for mobile robotics: An experimental ...
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We present an experimental comparison between two approaches to optimization of the rules for a fuzzy controller. More specifically, the problem is ...
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Experiments on a Pittsburgh-style fuzzy classifier system for mobile robotics. ABSTRACT We report on experiments designed to highlight the strengths and ...
Experiments on a Pittsburgh-style fuzzy classifier system for mobile robotics. ISIC 2002: 61-66. [c19]. view. electronic edition via DOI · unpaywalled version ...