Multiphase genetic programming: A case study in sumo maneuver evolution

Jiming LIU*, Shiwu Zhang

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

2 Citations (Scopus)


In this paper, we describe a new evolutionary computation approach, called multiphase genetic programming (MPGP). The special features of this approach lie in its variable-granularity representations of chromosomes and their corresponding genetic operations. In the paper, we provide an overview of the MPGP approach as well as details on how the sumo maneuver evolution experiments are carried out and how the MPGP-based case study differs from others.

Original languageEnglish
Pages (from-to)665-684
Number of pages20
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Issue number4
Publication statusPublished - Jun 2004

Scopus Subject Areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

User-Defined Keywords

  • Adaptive behavior
  • Multiphase genetic programming (MPGP)
  • Sumo maneuver evolution


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