Alhejali, Atif M and Lucas, Simon M (2013) Using genetic programming to evolve heuristics for a Monte Carlo Tree Search Ms Pac-Man agent. In: 2013 IEEE Conference on Computational Intelligence and Games (CIG), 2013-08-11 - 2013-08-13.
Alhejali, Atif M and Lucas, Simon M (2013) Using genetic programming to evolve heuristics for a Monte Carlo Tree Search Ms Pac-Man agent. In: 2013 IEEE Conference on Computational Intelligence and Games (CIG), 2013-08-11 - 2013-08-13.
Alhejali, Atif M and Lucas, Simon M (2013) Using genetic programming to evolve heuristics for a Monte Carlo Tree Search Ms Pac-Man agent. In: 2013 IEEE Conference on Computational Intelligence and Games (CIG), 2013-08-11 - 2013-08-13.
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 18% increase on its average score over the agent with random default policy. © 2013 IEEE.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Published proceedings: IEEE Conference on Computatonal Intelligence and Games, CIG |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 15 Jul 2015 13:29 |
Last Modified: | 24 Oct 2024 20:43 |
URI: | http://repository.essex.ac.uk/id/eprint/14374 |