@inproceedings{7621442588fa4012af3b39042f136567,
title = "Ensemble decision making in real-time games",
abstract = "This paper describes an Ensemble Agent for the classic arcade game Ms. Pac-Man. Our approach decomposes the problem into sub-goals. An expert agent is created for each sub-goal, with all experts reporting to a central arbiter. Our Ensemble Agent has achieved the AI world record for the arcade version of Ms. Pac-Man with a score of 162,280. For comparison, a MCTS-based monolithic agent was also created, based on the same accurate forward model that the Ensemble Agent uses, reaching a score of 115,180.",
keywords = "ensemble, mcts, Pac-Man, real-time, decision",
author = "Philip Rodgers and John Levine and Damien Anderson",
note = "Changed template to proceedings ET 10/2/20 Acceptance in SAN AAM: no embargo In scope of REF policy - has ISSN. ",
year = "2018",
month = oct,
day = "15",
doi = "10.1109/CIG.2018.8490401",
language = "English",
isbn = "978-1-5386-4360-0",
publisher = "IEEE",
booktitle = "2018 IEEE Conference on Computational Intelligence and Games (CIG)",
}