Title :
RAMP: A rule-based agent for Ms. Pac-Man
Author :
Fitzgerald, Alan ; Congdon, Clare Bates
Author_Institution :
Dept. of Comput. Sci., Univ. of Southern Maine, Portland, ME
Abstract :
RAMP is a rule-based agent for playing Ms. Pac-Man according to the rules stipulated in the 2008 World Congress on Computational Intelligence Ms. Pac-Man Competition. During the competition, our highest score was 15,970, outscoring the eleven other entrants in the competition. In runs reported here, RAMP achieves an average score over 10,000 and a high score of 18,560 across 100 runs; the highest score RAMP has achieved to date is 19,000. These are scores that are better than typical human novice players, including the paper authors themselves. The system was designed to have an evolutionary component, however, this was not developed in time for the competition, which instead used hand-coded rules. We have found the process of tuning the rule sets and accompanying parameters to be a time consuming and inexact process that is expected to benefit from an evolutionary computation approach. This paper describes our initial implementation as well as our progress towards adding an evolutionary computation component to enable the agent learn to play the game.
Keywords :
computer games; evolutionary computation; learning (artificial intelligence); software agents; Ms Pac-Man; artificial agent learning; evolutionary computation; hand-coded rule; rule-based agent; Computational intelligence; Computer science; Decision making; Evolutionary computation; Feature extraction; Game theory; Humans; USA Councils; Writing;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983274