AIIDE Artifact Archive

Analysis of Statistical Forward Planning Methods in Pommerman

Authors:
Date Archived: 8 October 2019
Accompanying Paper: Analysis of Statistical Forward Planning Methods in Pommerman
Artifact URL: http://aiide.org/artifacts/files/pommerman.zip
Alternative URL: https://github.com/GAIGResearch/java-pommerman
Description:

Pommerman is a complex multi-player and partially observable game where agents try to be the last standing to win. This game poses very interesting challenges to AI, such as collaboration, learning and planning. We compare two statistical forward planning algorithms, Monte Carlo Tree Search (MCTS) and Rolling Horizon Evolutionary Algorithm (RHEA) in Pommerman.

How to Cite This Artifact

The examples below show how to cite this page, but when referring to this work, many authors will prefer that you cite the accompanying paper linked above.

AAAI Style
Perez-Liebana, D. et al. 2019. Analysis of Statistical Forward Planning Methods in Pommerman. http://aiide.org/artifacts/pommerman. Accessed 23 November 2024.
IEEE Style
D. Perez-Liebana et al., "Analysis of Statistical Forward Planning Methods in Pommerman," 2019. [Online]. Available: http://aiide.org/artifacts/pommerman. [Accessed Nov 23, 2024].
BiBTeX Entry
@misc{pommerman,
	author={Perez-Liebana, Diego and Gaina, Raluca D. and Drageset, Olve and Ilhan, Ercüment and Balla, Martin and Lucas, Simon M.},
	title={Analysis of Statistical Forward Planning Methods in Pommerman},
	howpublished={\url{http://aiide.org/artifacts/pommerman}},
	year={2019},
	note={Accessed 23 November 2024}
}