A Monte-Carlo approach for ghost avoidance in the Ms. Pac-Man game

Bruce K.B. Tong, Chi Wan Sung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Citations (Scopus)

Abstract

Ms. Pac-Man is a challenging, classic arcade game that provides an interesting platform for Artificial Intelligence (AI) research. This paper reports the first Monte-Carlo approach to develop a ghost avoidance module of an intelligent agent that plays the game. Our experimental results show that the look-ahead ability of Monte-Carlo simulation often prevents Ms. Pac-Man being trapped by ghosts and reduces the chance of losing Ms. Pac-Man's life significantly. Our intelligent agent has achieved a high score of around 21,000. It is sometimes capable of clearing the first three stages and playing at the level of a novice human player.

Original languageEnglish
Title of host publication2nd International IEEE Consumer Electronic Society Games Innovation Conference, ICE-GIC 2010
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2nd International IEEE Consumer Electronic Society Games Innovation Conference, ICE-GIC 2010 - Hong Kong, China
Duration: 21 Dec 201023 Dec 2010

Publication series

Name2nd International IEEE Consumer Electronic Society Games Innovation Conference, ICE-GIC 2010

Conference

Conference2nd International IEEE Consumer Electronic Society Games Innovation Conference, ICE-GIC 2010
Country/TerritoryChina
CityHong Kong
Period21/12/1023/12/10

Keywords

  • Competition
  • Computational intelligence
  • Game
  • Monte-Carlo simulation
  • Ms. Pac-Man

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