Expressive genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Lee Spector",
  title =        "Expressive genetic programming",
  booktitle =    "GECCO 2014 Advanced tutorials",
  year =         "2014",
  editor =       "Mengjie Zhang",
  isbn13 =       "978-1-4503-2881-4",
  keywords =     "genetic algorithms, genetic programming",
  pages =        "581--606",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Vancouver, BC, Canada",
  URL =          "",
  DOI =          "doi:10.1145/2598394.2605350",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "The language in which evolving programs are expressed
                 can have significant impacts on the problem-solving
                 capabilities of a genetic programming system. These
                 impacts stem both from the absolute computational power
                 of the languages that are used, as elucidated by formal
                 language theory, and from the ease with which various
                 computational structures can be produced by random code
                 generation and by the action of genetic operators.
                 Highly expressive languages can facilitate the
                 evolution of programs for any computable function
                 using, when appropriate, multiple data types, evolved
                 subroutines, evolved control structures, evolved data
                 structures, and evolved modular program and data
                 architectures. In some cases expressive languages can
                 even support the evolution of programs that express
                 methods for their own reproduction and variation (and
                 hence for the evolution of their offspring).

                 This tutorial will begin with a comparative survey of
                 approaches to the evolution of programs in expressive
                 programming languages ranging from machine code to
                 graphical and grammatical representations. Within this
                 context it will then provide a detailed introduction to
                 the Push programming language, which was designed
                 specifically for expressiveness and specifically for
                 use in genetic programming systems. Push programs are
                 syntactically unconstrained but can nonetheless make
                 use of multiple data types and express arbitrary
                 control structures, supporting the evolution of
                 complex, modular programs in a particularly simple and
                 flexible way. The Push language will be described and
                 demonstrated, and ten years of Push-based research,
                 including the production of human-competitive results,
                 will be briefly surveyed. The tutorial will conclude
                 with a discussion of recent enhancements to Push that
                 are intended to support the evolution of complex and
                 robust software systems.",
  notes =        "Also known as \cite{2605350} Distributed at

Genetic Programming entries for Lee Spector