What Can Automatic Programming Learn from Theoretical Computer Science?

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

  author =       "Colin G. Johnson",
  booktitle =    "The 2002 U.K. Workshop on Computational Intelligence
  title =        "What Can Automatic Programming Learn from Theoretical
                 Computer Science?",
  year =         "2002",
  editor =       "Xin Yao",
  address =      "Birmingham, U.K.",
  month =        "2-4 " # sep,
  organisation = "eunite",
  keywords =     "genetic algorithms, genetic programming, SBSE",
  URL =          "http://kar.kent.ac.uk/id/eprint/13729",
  URL =          "http://kar.kent.ac.uk/13729/1/WhatColin1.pdf",
  size =         "7 pages",
  abstract =     "This paper considers two (seemingly) radically
                 different perspectives on the construction of software.
                 On one hand, search-based heuristics such as genetic
                 programming. On the other hand, the theories of
                 programming which underpin mathematical program
                 analysis and formal methods. The main part of the paper
                 surveys possible links between these perspectives. In
                 particular the contrast between inductive and deductive
                 approaches to software construction are studied, and
                 various suggestions are made as to how randomised
                 search heuristics can be combined with formal
                 approaches to software construction without
                 compromising the rigorous provability of the results.
                 The aim of the ideas proposed is to improve the
                 efficiency, effectiveness and safety of search-based
                 automatic programming.",
  notes =        "http://www.cs.bham.ac.uk/~jxb/UKCI/program.shtml",

Genetic Programming entries for Colin G Johnson