DocumentCode :
552531
Title :
Evolutionary neural network for ghost in Ms. Pac-Man
Author :
Dai, Jia-yue ; Li, Yan ; Chen, Jun-Fen ; Zhang, Feng
Author_Institution :
Machine Learning Center, Hebei Univ., Baoding, China
Volume :
2
fYear :
2011
fDate :
10-13 July 2011
Firstpage :
732
Lastpage :
736
Abstract :
Ms. Pac-Man is a popular chasing and evading game and the ghost character in the game is controlled by script. This article evolved an evolutionary neural network for the red ghost to chase Pac-Man. Red ghost´ position, Pac-Man´s position and Pac-Man´s state are considered to be the inputs of the neural network, and the output is the direction of Red ghost to move in the next step. We also proposed a fitness function to raise capture ability in evolution so that the Red ghost learns by itself in simulation. Experimental results show that the agent learns well and plays better in teamwork than the traditional script controlled ghost.
Keywords :
computer games; evolutionary computation; neural nets; team working; Ms.Pac-Man game; Red ghost character; capture ability; evolutionary neural network; teamwork; Biological cells; Biological neural networks; Cybernetics; Games; Learning systems; Machine learning; Teamwork; Chasing and evading game; Evolutionary neural network; Game AI; Pac-Man;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
ISSN :
2160-133X
Print_ISBN :
978-1-4577-0305-8
Type :
conf
DOI :
10.1109/ICMLC.2011.6016831
Filename :
6016831
Link To Document :
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