Book ChapterDOI
A Grammar-Based Genetic Algorithm
Hendrik James Antonisse
- Vol. 1, pp 193-204
TLDR
A reformulation of the genetic algorithm is proposed that makes it appropriate to any representation that can be cast in a formal grammar, and concentrates on the modifications required to make the space of legal structures closed under the crossover operator.Abstract:
High-level syntactically-based representations pose problems for applying the GA because it is hard to construct crossover operators that always result in legal offspring. This paper proposes a reformulation of the genetic algorithm that makes it appropriate to any representation that can be cast in a formal grammar. This reformulation is consistent with recent reinterpretations of GA foundations in set-theoretic terms, and concentrates on the modifications required to make the space of legal structures closed under the crossover operator. The analysis places no restriction on the form of the grammars.read more
Citations
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An Exploration of Grammars in Grammatical Evolution
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References
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Book
Genetic Algorithms and Simulated Annealing
TL;DR: A detergent composition mainly for automatic laundering machines which comprises, on the basis of 100 parts by weight of total composition, at least 60 parts of soap and no more than 10 parts of a mixture of surfactants which impart an excellent detergent ability and foam control even in very soft waters and non-polluting properties.
Proceedings Article
Adapting operator probabilities in genetic algorithms
TL;DR: This dissertation describes an empirical investigation into whether it can be convincingly argued that these probabilities should vary over the course of a genetic algorithm run so as to account for changes in the ability of the operators to produce children of increased strength.
Proceedings Article
Scheduling Problems and Traveling Salesmen: The Genetic Edge Recombination Operator
Journal ArticleDOI
Credit assignment in rule discovery systems based on genetic algorithms
TL;DR: In this article, the credit assignment problem that arises when long sequences of rules fire between successive external rewards is addressed, and two distinct approaches to rule learning with genetic algorithms have been previously reported, each approach offering a useful solution to a different level of credit assignment.