Mixing Search Strategies for Multi-Player Games

Abstract

There are two basic approaches to generalize the propagation mechanism of the two-player Minimax search algorithm to multi-player (3 or more) games: the MaxN algorithm and the Paranoid algorithm. The main shortcoming of these approaches is that their strategy is fixed. In this paper we suggest a new approach (called MP-Mix) that dynamically changes the propagation strategy based on the players' relative strengths between MaxN, Paranoid and a newly presented offensive strategy. In addition, we introduce the Opponent Impact factor for multi-player games, which measures the players' ability to impact their opponents' score, and show its relation to the relative performance of our new MP-Mix strategy. Experimental results show that MP-Mix outperforms all other approaches under most circumstances. Inon Zuckerman, Ariel Felner, Sarit Kraus

Cite

Text

Zuckerman et al. "Mixing Search Strategies for Multi-Player Games." International Joint Conference on Artificial Intelligence, 2009.

Markdown

[Zuckerman et al. "Mixing Search Strategies for Multi-Player Games." International Joint Conference on Artificial Intelligence, 2009.](https://mlanthology.org/ijcai/2009/zuckerman2009ijcai-mixing/)

BibTeX

@inproceedings{zuckerman2009ijcai-mixing,
  title     = {{Mixing Search Strategies for Multi-Player Games}},
  author    = {Zuckerman, Inon and Felner, Ariel and Kraus, Sarit},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2009},
  pages     = {646-652},
  url       = {https://mlanthology.org/ijcai/2009/zuckerman2009ijcai-mixing/}
}