Efficient Markov chain model of machine code program execution and halting
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InCollection{poli:2006:GPTP,
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author = "Riccardo Poli and William B. Langdon",
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title = "Efficient Markov chain model of machine code program
execution and halting",
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booktitle = "Genetic Programming Theory and Practice {IV}",
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year = "2006",
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editor = "Rick L. Riolo and Terence Soule and Bill Worzel",
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volume = "5",
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series = "Genetic and Evolutionary Computation",
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pages = "257--278",
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address = "Ann Arbor",
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month = "11-13 " # may,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-387-33375-4",
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URL = "http://www.cs.essex.ac.uk/staff/poli/papers/GPTP2006.pdf",
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DOI = "doi:10.1007/978-0-387-49650-4_16",
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size = "16 pages",
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abstract = "We focus on the halting probability and the number of
instructions executed by programs that halt for
Turing-complete register based machines. The former
represents the fraction of programs which provide
useful results in a machine code genetic programming
system. The latter determines run time and whether or
not the distribution of program functionality has
reached a fixed-point. We describe a Markov chain model
of program execution and halting which accurately fits
empirical data allowing us to efficiently estimate the
halting probability and the numbers of instructions
executed for programs including millions of
instructions. We also discuss how this model can be
applied to improve GP practice.",
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notes = "Video at (broken Nov 2020)
http://video.google.com/videoplay?docid=-3432013567298818193
(broken Nov 2020)
http://cswww.essex.ac.uk/staff/rpoli/gptp06/ (high
resolution)",
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notes = "part of \cite{Riolo:2006:GPTP} Published Jan 2007
after the workshop",
- }
Genetic Programming entries for
Riccardo Poli
William B Langdon
Citations