Automatic Generation and Evaluation of Recombination Games

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

@PhdThesis{CameronBrowne:thesis,
  author =       "Cameron Browne",
  title =        "Automatic Generation and Evaluation of Recombination
                 Games",
  school =       "Faculty of Information Technology, Queensland
                 University of Technology",
  year =         "2008",
  address =      "Australia",
  month =        feb,
  keywords =     "genetic algorithms, genetic programming,
                 Combinatorial, Games, Design, Aesthetics, Evolutionary,
                 Search, Yavalath",
  URL =          "http://www.cameronius.com/cv/publications/thesis-2.47.zip",
  size =         "251 pages",
  abstract =     "Many new board games are designed each year, ranging
                 from the unplayable to the truly exceptional. For each
                 successful design there are untold numbers of failures;
                 game design is something of an art. Players generally
                 agree on some basic properties that indicate the
                 quality and viability of a game, however these
                 properties have remained subjective and open to
                 interpretation.

                 The aims of this thesis are to determine whether such
                 quality criteria may be precisely defined and
                 automatically measured through self-play in order to
                 estimate the likelihood that a given game will be of
                 interest to human players, and whether this information
                 may be used to direct an automated search for new games
                 of high quality. Combinatorial games provide an
                 excellent test bed for this purpose as they are
                 typically deep yet described by simple well defined
                 rule sets.

                 To test these ideas, a game description language was
                 devised to express such games and a general game system
                 implemented to play, measure and explore them. Key
                 features of the system include modules for measuring
                 statistical aspects of self-play and synthesising new
                 games through the evolution of existing rule
                 sets.

                 Experiments were conducted to determine whether
                 automated game measurements correlate with rankings of
                 games by human players, and whether such correlations
                 could be used to inform the automated search for new
                 high quality games. The results support both hypotheses
                 and demonstrate the emergence of interesting new rule
                 combinations.",
  notes =        "Reviewed by \cite{Althoefer:2010:ICGA}",
}

Genetic Programming entries for Cameron Browne

Citations