Evolutionary Game-Theoretical Analysis for General Multiplayer Asymmetric Games

• URL: http://arxiv.org/abs/2206.11114v1
• Date: Wed, 22 Jun 2022 14:06:23 GMT
• Title: Evolutionary Game-Theoretical Analysis for General Multiplayer Asymmetric Games
• Authors: Xinyu Zhang, Peng Peng, Yushan Zhou, Haifeng Wang, Wenxin Li
• Abstract summary: We fill the gap between payoff table and dynamic analysis without any inaccuracy. We compare our method with the state-of-the-art in some classic games.
• Score: 22.753799819424785
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Evolutionary game theory has been a successful tool to combine classical game theory with learning-dynamical descriptions in multiagent systems. Provided some symmetric structures of interacting players, many studies have been focused on using a simplified heuristic payoff table as input to analyse the dynamics of interactions. Nevertheless, even for the state-of-the-art method, there are two limits. First, there is inaccuracy when analysing the simplified payoff table. Second, no existing work is able to deal with 2-population multiplayer asymmetric games. In this paper, we fill the gap between heuristic payoff table and dynamic analysis without any inaccuracy. In addition, we propose a general framework for $m$ versus $n$ 2-population multiplayer asymmetric games. Then, we compare our method with the state-of-the-art in some classic games. Finally, to illustrate our method, we perform empirical game-theoretical analysis on Wolfpack as well as StarCraft II, both of which involve complex multiagent interactions.

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