Efficient Evolution of Machine Code for CISC Architectures using Instruction Blocks and Homologous Crossover
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InCollection{nordin:1999:aigp3,
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author = "Peter Nordin and Wolfgang Banzhaf and
Frank D. Francone",
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title = "Efficient Evolution of Machine Code for {CISC}
Architectures using Instruction Blocks and Homologous
Crossover",
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booktitle = "Advances in Genetic Programming 3",
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publisher = "MIT Press",
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year = "1999",
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editor = "Lee Spector and William B. Langdon and
Una-May O'Reilly and Peter J. Angeline",
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pages = "275--299",
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chapter = "12",
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address = "Cambridge, MA, USA",
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month = jun,
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-262-19423-6",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/aigp3/ch12.pdf",
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URL = "http://www.aimlearning.com/aigp31.pdf",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.9365",
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DOI = "doi:10.7551/mitpress/1110.003.0017",
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abstract = "This chapter describes recent advances in genetic
programming of machine code. Evolutionary program
induction of binary machine code is one of the fastest
1 GP methods and the most well studied linear approach.
The technique has previously been known as Compiling
Genetic Programming System (CGPS) but to avoid
confusion with methods using an actual compiler and to
separate the system from the method, the name has been
changed to Automatic Induction of Machine Code with
Genetic Programming (AIM-GP). AIM-GP stores individuals
as a linear string of native binary machine code, which
is directly executed by the processor. The absence of
an interpreter and complex memory handling allows
increased speed of several orders of magnitudes. AIM-GP
has so far been applied to processors with a fixed
instruction length (RISC) using integer arithmetics.
This chapter describes several new advances to the
AIM-GP method which are important for the applicability
of the technique. Such advances include enabling the
induction of code for CISC processors such as the most
widespread computer architecture INTEL x86 as well as
JAVA and many embedded processors. The new technique
also makes AIM-GP more portable in general and
simplifies 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. We also discuss the benefits and drawbacks
of register machine GP versus tree-based GP. This
chapter is meant to be a directed towards the
practitioner, who wants to extend AIM-GP to new
architectures and application domains.",
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notes = "AiGP3 See http://cognet.mit.edu",
- }
Genetic Programming entries for
Peter Nordin
Wolfgang Banzhaf
Frank D Francone
Citations