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EAAI
2006
161views more  EAAI 2006»
13 years 7 months ago
Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers
Type-2 fuzzy sets, which are characterized by membership functions (MFs) that are themselves fuzzy, have been attracting interest. This paper focuses on advancing the understandin...
Dongrui Wu, Woei Wan Tan
GECCO
2003
Springer
14 years 20 days ago
Generative Representations for Evolving Families of Designs
Abstract. Since typical evolutionary design systems encode only a single artifact with each individual, each time the objective changes a new set of individuals must be evolved. Wh...
Gregory Hornby
ISCC
2006
IEEE
188views Communications» more  ISCC 2006»
14 years 1 months ago
Dejong Function Optimization by Means of a Parallel Approach to Fuzzified Genetic Algorithm
Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually in...
Ebrahim Bagheri, Hossein Deldari
AEI
1999
110views more  AEI 1999»
13 years 7 months ago
Self-tuning fuzzy controller design using genetic optimisation and neural network modelling
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
Duc Truong Pham, Dervis Karaboga
GECCO
2009
Springer
175views Optimization» more  GECCO 2009»
14 years 2 days ago
Evolving soft robotic locomotion in PhysX
Given the complexity of the problem, genetic algorithms are one of the more promising methods of discovering control schemes for soft robotics. Since physically embodied evolution...
John Rieffel, Frank Saunders, Shilpa Nadimpalli, H...