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42
A Selection Scheme for Excluding Defective Rules of Evolutionary Fuzzy Path Planning
"... Abstract. This paper proposes a new selection mechanism in evolutionary algorithm for fuzzy systems that can be applied to robot learning of shooting ability in robot soccer. In generic evolutionary algorithms, evaluation and selection are performed on the chromosome level, where a selected chromos ..."
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chromosome may include non-effective or bad genes. This may lead to an increase in the uncertainty of the solutions. To solve this problem, we propose a rule-scoring method for gene level selection, which grades genes at the same position in the chromosomes. This method is applied to a fuzzy path planner
Recombinant rule selection in evolutionary algorithm for fuzzy path planner of robot soccer
- in: Advances in Artificial Intelligence, KI 2006
, 2007
"... Abstract. A rule selection scheme of evolutionary algorithm is pro-posed to design fuzzy path planner for shooting ability in robot soccer. The fuzzy logic is good for the system that works with ambiguous in-formation. Evolutionary algorithm is employed to deal with difficulty and tediousness in der ..."
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Cited by 2 (0 self)
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Abstract. A rule selection scheme of evolutionary algorithm is pro-posed to design fuzzy path planner for shooting ability in robot soccer. The fuzzy logic is good for the system that works with ambiguous in-formation. Evolutionary algorithm is employed to deal with difficulty and tediousness
ANY-TIME FUZZY CONTROLLER
, 2006
"... Fuzzy logic has been successfully applied in various fields. However, as fuzzy controllers increase in size and complexity, the number of control rules increases exponentially and real-time behavior becomes more difficult. This thesis introduces an any-time fuzzy controller. Much work has been done ..."
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of fuzzy control. Popular aggregation and defuzzification methods (max-min, sum-product, MOM and COG) are first shown to satisfy these constraints, and then three linearization methods are presented. Linearization methods are used to reorder fuzzy rules base such that a reordered rule base would result
Automatic program repair with evolutionary computation,”
- Commun. ACM,
, 2010
"... Abstract There are many methods for detecting and mitigating software errors but few generic methods for automatically repairing errors once they are discovered. This paper highlights recent work combining program analysis methods with evolutionary computation to automatically repair bugs in off-th ..."
Abstract
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Cited by 34 (5 self)
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APPROACH The core of our method is an evolutionary algorithm that repairs programs by selectively searching through the space of related program variants until it discovers one that avoids known defects and retains key functionality. We use a novel GP representation and make assumptions about the probable
POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES PAR
"... 2010 to my wife, Joyce, and my family...- Résumé- ..."
Chapter 12 Rough Sets and Rough Logic: A KDD Perspective
"... Abstract Basic ideas of rough set theory were proposed by Zdzis law Pawlak [85, 86] in the early 1980’s. In the ensuing years, we have witnessed a systematic, world–wide growth of interest in rough sets and their applications. The main goal of rough set analysis is induction of approximations of con ..."
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Abstract Basic ideas of rough set theory were proposed by Zdzis law Pawlak [85, 86] in the early 1980’s. In the ensuing years, we have witnessed a systematic, world–wide growth of interest in rough sets and their applications. The main goal of rough set analysis is induction of approximations
Special Issue on Intelligent Control and Robotics
"... The momentum of real industrial applications has accelerated the development of fuzzy control, neural-network based control, evolutionary control etc. During the last decade, several computational intelligence techniques haven been also incorporated into the intelligent robotics research domain. The ..."
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of mobile robots. The algorithm consists of an obstacle avoidance scheme that is introduced to generate efficient initial population and domain heuristic knowledge based crossover, mutation, refinement and deletion operators that are tailored to fit path planning for mobile robots. Furthermore, a fuzzy
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