TY - GEN
T1 - A Monte-Carlo approach for the endgame of Ms. Pac-Man
AU - Tong, Bruce Kwong Bun
AU - Ma, Chun Man
AU - Sung, Chi Wan
PY - 2011
Y1 - 2011
N2 - Ms. Pac-Man is a challenging video game which provides an interesting platform for artificial intelligence and computational intelligence research. This paper introduces the novel concept of path testing and reports an effective Monte-Carlo approach to develop an endgame module of an intelligent agent that plays the game. Our experimental results show that the proposed method often helps Ms. Pac-Man to eat pills effectively in the endgame. It enables the agent to advance to higher stages and earn more scores. Our agent with the endgame module has achieved a 20% increase in average score over the same agent without the module.
AB - Ms. Pac-Man is a challenging video game which provides an interesting platform for artificial intelligence and computational intelligence research. This paper introduces the novel concept of path testing and reports an effective Monte-Carlo approach to develop an endgame module of an intelligent agent that plays the game. Our experimental results show that the proposed method often helps Ms. Pac-Man to eat pills effectively in the endgame. It enables the agent to advance to higher stages and earn more scores. Our agent with the endgame module has achieved a 20% increase in average score over the same agent without the module.
UR - http://www.scopus.com/inward/record.url?scp=80054038844&partnerID=8YFLogxK
U2 - 10.1109/CIG.2011.6031983
DO - 10.1109/CIG.2011.6031983
M3 - Conference contribution
AN - SCOPUS:80054038844
SN - 9781457700095
T3 - 2011 IEEE Conference on Computational Intelligence and Games, CIG 2011
SP - 9
EP - 15
BT - 2011 IEEE Conference on Computational Intelligence and Games, CIG 2011
T2 - 2011 7th IEEE International Conference on Computational Intelligence and Games, CIG 2011
Y2 - 31 August 2011 through 3 September 2011
ER -