2 citations · 4 across the 15 of their papers we have counts for
3 papers · 1 filter
Approximately Solving Continuous-Time Mean Field Games with Finite State Spaces
Yannick Eich, Christian Fabian, Kai Cui +1
Mean field games (MFGs) offer a powerful framework for modeling large-scale multi-agent systems. This paper addresses MFGs formulated in continuous time with discrete state spaces,…
Bounded Rationality Equilibrium Learning in Mean Field Games
Yannick Eich, Christian Fabian, Kai Cui +1
Mean field games (MFGs) tractably model behavior in large agent populations. The literature on learning MFG equilibria typically focuses on finding Nash equilibria (NE), which assu…
Learning Discrete-Time Major-Minor Mean Field Games
Kai Cui, Gökçe Dayanıklı, Mathieu Laurière +3
Recent techniques based on Mean Field Games (MFGs) allow the scalable analysis of multi-player games with many similar, rational agents. However, standard MFGs remain limited to ho…