• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

DMCA

Cached

  • Download as a PDF

Download Links

  • [studentweb.cs.bham.ac.uk]
  • [www.cs.bham.ac.uk]
  • [www.cs.bham.ac.uk]

  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Peter Nordin , Wolfgang Banzhaf , Frank D. Francone
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Nordin_,
    author = {Peter Nordin and Wolfgang Banzhaf and Frank D. Francone},
    title = {},
    year = {}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

Evolutionary program induction using binary machine code is the fastest known Genetic Programming method. It is, in addition, the most well studied Genetic Programming system that uses a linear genome. This chapter describes recent advances in genetic programming of machine code. Evolutionary program induction using binary machine code was originally referred to as Compiling Genetic Programming System (CGPS). For clarity, the name was changed in early 1998 to Automatic Induction of Machine Code—Genetic Programming (AIM-GP). AIM-GP stores evolved programs as linear strings of native binary machine code, which are directly executed by the processor. The absence of an interpreter and complex memory handling increases the speed of AIM-GP by about two orders of magnitude. AIM-GP has so far been applied to processors with a fixed instruction length (RISC) using integer and floating-point arithmetic. We also describe several recent advances in the AIM-GP technology. Such advances include enabling the induction of code for CISC processors such as the INTEL x86 as well as JAVA and many embedded processors. The new techniques also make AIM-GP more portable in general and simplify the adaptation to any processor architecture. Other additions include the use of floating point instructions, control flow instructions, ADFs and new genetic operators e.g. aligned homologous crossover. This chapter also discusses the benefits

Keyphrases

evolutionary program induction    binary machine code    linear genome    homologous crossover    linear string    aim-gp technology    many embedded processor    cisc processor    machine code genetic programming    complex memory handling    several recent advance    aim-gp store    genetic programming    machine code    studied genetic programming system    native binary machine code    recent advance    compiling genetic programming system    intel x86    new genetic operator    genetic programming method    automatic induction    processor architecture    control flow instruction    new technique    point instruction    fixed instruction length   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University