Off-Line Evolution of Behaviour for Autonomous Agents in Real-Time Computer Games

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

@InProceedings{anderson:ppsn2002:pp689,
  author =       "Eike Falk Anderson",
  title =        "Off-Line Evolution of Behaviour for Autonomous Agents
                 in Real-Time Computer Games",
  booktitle =    "Parallel Problem Solving from Nature - PPSN VII",
  address =      "Granada, Spain",
  month =        "7-11 " # sep,
  pages =        "689--699",
  year =         "2002",
  editor =       "Juan J. Merelo-Guervos and Panagiotis Adamidis and 
                 Hans-Georg Beyer and Jose-Luis Fernandez-Villacanas and 
                 Hans-Paul Schwefel",
  number =       "2439",
  series =       "Lecture Notes in Computer Science, LNCS",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, Games,
                 Machine Learning, Fitness Evaluation",
  ISBN =         "3-540-44139-5",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2439&spage=689",
  DOI =          "doi:10.1007/3-540-45712-7_66",
  abstract =     "This paper describes and analyses a series of
                 experiments intended to evolve a player for a variation
                 of the classic arcade game Asteroids TM using steady
                 state genetic programming. The player's behaviour is
                 defined using a LISP like scripting language. While the
                 game interprets scripts in real-time, such scripts are
                 evolved off-line by a second program which simulates
                 the realtime application. This method is used, as
                 on-line evolution of the players would be too time
                 consuming. A successful player needs to satisfy
                 multiple conflicting objectives. This problem is
                 addressed by the use of an automatically defined
                 function (ADF) for each of these objectives in
                 combination with task specific fitness functions. The
                 overall fitness of evolved scripts is evaluated by a
                 conventional fitness function. In addition to that,
                 each of the ADFs is evaluated with a separate fitness
                 function, tailored specifically to the objective that
                 needs to be satisfied by that ADF.",
}

Genetic Programming entries for Eike Falk Anderson

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