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Publication Detail
Using Data Structures within Genetic Programming
  • Publication Type:
  • Authors:
    Langdon WB
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  • Place of publication:
    Gower Street, London, WC1E 6BT, UK
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  • Notes:
    keywords: genetic algorithms, genetic programming, context free language induction, Reverse Polish Expressions, automatic code generation, Automatic Programming, Machine Learning, Artificial Evolution, Data Structures, Object Oriented Programming, Push down Stack, Automatically Defined Functions (ADF), Pareto fitness, Demes notes: Accepted for presentation at GP96. Updated version in proceedings and url, see \citeLangdon:1996:usedata size: 10 pages
In earlier work we showed that GP can automatically generate simple data types (stacks, queues and lists). The results presented herein show, in some cases, provision of appropriately structured memory can indeed be advantageous to GP in comparison with directly addressable indexed memory. Three “classic” problems are solved. The first two require the GP to distinguish between sentences that are in a language and those that are not given positive and negative training examples of the language. The two languages are, correctly nested brackets and a Dyck language (correctly nested brackets of different types). The third problem is to evaluate integer Reverse Polish (postfix) expressions. Comparisons are made between GP attempting to solve these problems when provided with indexed memory or with stack data structures.
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