Probabilistic Pattern Matching and the Genetic Programming of Stochastic Regular Expressions

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@Article{Ross:2000:ppmGP,

• author = "Brian J. Ross",
• title = "Probabilistic Pattern Matching and the Genetic Programming of Stochastic Regular Expressions",
• journal = "International Journal of Applied Intelligence",
• year = "2000",
• volume = "3",
• number = "3",
• pages = "285--300",
• month = nov # "/" # dec,
• ISSN = "0924-669X",
• DOI = "doi:10.1023/A:1026524328760",
• keywords = "genetic algorithms, genetic programming, stochastic regular expressions",
• abstract = "The use of genetic programming for probabilistic pattern matching is investigated. A stochastic regular expression language is used. The language features a statistically sound semantics, as well as a syntax that promotes efficient manipulation by genetic programming operators. An algorithm for efficient string recognition based on approaches in conventional regular language recognition is used. When attempting to recognize a particular test string, the recognition algorithm computes the probabilities of generating that string and all its prefixes with the given stochastic regular expression. To promote efficiency, intermediate computed probabilities that exceed a given cut-off value will pre-empt particular interpretation paths, and hence prune unconstructive interpretation. A few experiments in recognising stochastic regular languages are discussed. Application of the technology in bioinformatics is in progress.",
• notes = "DCTG-GP context free grammar. p294 fitness modelled on chi-squared test. Tomita language. Stochastic regular grammar.",

}

Genetic Programming entries for Brian J Ross

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