Using genetic programming to evolve heuristics for a Monte Carlo Tree Search Ms Pac-Man agent

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Alhejali:2013:CIG,
  author =       "Atif M. Alhejali and Simon M. Lucas",
  booktitle =    "IEEE Conference on Computational Intelligence in Games
                 (CIG 2013)",
  title =        "Using genetic programming to evolve heuristics for a
                 Monte Carlo Tree Search Ms Pac-Man agent",
  year =         "2013",
  month =        aug,
  abstract =     "Ms Pac-Man is one of the most challenging test beds in
                 game artificial intelligence (AI). Genetic programming
                 and Monte Carlo Tree Search (MCTS) have already been
                 successful applied to several games including Pac-Man.
                 In this paper, we use Monte Carlo Tree Search to create
                 a Ms Pac-Man playing agent before using genetic
                 programming to enhance its performance by evolving a
                 new default policy to replace the random agent used in
                 the simulations. The new agent with the evolved default
                 policy was able to achieve an 18percent increase on its
                 average score over the agent with random default
                 policy.",
  keywords =     "genetic algorithms, genetic programming, Monte Carlo
                 methods, artificial intelligence, computer games, tree
                 searching, Al, MCTS, Monte Carlo tree search Ms Pac-Man
                 agent, evolved default policy, game artificial
                 intelligence, random agent, random default policy,
                 Equations, Games, Mathematical model, Monte Carlo
                 methods, Sociology, Monte Carlo Tree Search, Pac-Man",
  DOI =          "doi:10.1109/CIG.2013.6633639",
  ISSN =         "2325-4270",
  notes =        "Also known as \cite{6633639}",
}

Genetic Programming entries for Atif M Alhejali Simon M Lucas

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