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Parallel Genetic Programming

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UK Parallel ’96

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Abstract

A parallel implementation of Genetic Programming using PVM is described. Two different topologies for parallel implementation of GP are examined. Both of them are based on the island model for evolutionary algorithms. It is shown that considerable speedup of the GP execution can be achieved and that the parallel versions of the algorithm are very suitable for complex, time consuming problems.

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References

  1. A. Geist, A. Beguelin, J. Dongarra, W. Jiang, E. Manchek, and V. Sunderam. PVM: Parallel Virtual Machine A Users’ Guide and Tutorial for Networked Parallel Computing. MIT Press, 1994.

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  2. David E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, 1989.

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  4. John H. Holland. Adaptation in Natural and Artificial Systems. The University of Michigan Press, 1975.

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  5. John Koza and David Andre. Parallel genetic programming on a network of transputers. Technical Report CS-TR-95–1542, Stanford University, 1995.

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  6. John R. Koza. Genetic Programming. MIT Press, 1982.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Brunel University, London, UK

    Dimitris C. Dracopoulos & Duncan Self

Authors
  1. Dimitris C. Dracopoulos
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  2. Duncan Self
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Surrey, GU2 5XH, Guildford, Surrey, UK

    Chris Jesshope PhD, MSc, BSc  & Shasha Shafarenko MSc, PhD  & 

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© 1996 Springer-Verlag London Limited

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Dracopoulos, D.C., Self, D. (1996). Parallel Genetic Programming. In: Jesshope, C., Shafarenko, S. (eds) UK Parallel ’96. Springer, London. https://doi.org/10.1007/978-1-4471-1504-5_11

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  • DOI: https://doi.org/10.1007/978-1-4471-1504-5_11

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-76068-9

  • Online ISBN: 978-1-4471-1504-5

  • eBook Packages: Springer Book Archive

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