This method can also be applied to other games, including Leduc poker, which is described in detail in the paper. In all of these situations, the method proves to be mathematically simple, allowing a rapid and straightforward analysis of asymmetric games that we hope will also help our understanding of various dynamic systems, including multi-agent environments.
UPDATE 20/03/18: Our latest paper, forthcoming at the Autonomous Agents and Multi-Agent Systems conference (AAMAS), builds on the Scientific Reports paper outlined above. A Generalised Method for Empirical Game Theoretic Analysis introduces a general method to perform empirical analysis of multi-agent interactions, both in symmetric and asymmetric games. The method allows to understand how multi-agent strategies interact, what the attractors are and what the basins of attraction look like, giving an intuitive understanding for the strength of the involved strategies. Furthermore, it explains how many data samples to consider in order to guarantee that the equilibria of the approximating game are sufficiently reliable. We apply the method to several domains, including AlphaGo, Colonel Blotto and Leduc poker.
Read the original Scientific Reports paper here.
Read the follow-up AAMAS paper here.
The Scientific Reports paper is authored by Karl Tuyls, Julien Perolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Leibo, Toby Ord, Thore Graepel and Shane Legg. The AAMAS paper is authored by Karl Tuyls, Julien Perolat, Marc Lanctot, Joel Leibo and Thore Graepel.
Source: https://deepmind.com/blog/article/game-theory-insights-asymmetric-multi-agent-games