Finding General Equilibria in Many-Agent Economic Simulations Using Deep Reinforcement Learning. (arXiv:2201.01163v1 [cs.GT])

Real economies can be seen as a sequential imperfect-information game with
many heterogeneous, interacting strategic agents of various agent types, such
as consumers, firms, and governments. Dynamic general equilibrium models are
common economic tools to model the economic activity, interactions, and
outcomes in such systems. However, existing analytical and computational
methods struggle to find explicit equilibria when all agents are strategic and
interact, while joint learning is unstable and challenging. Amongst others, a
key reason is that the actions of …

arxiv economic equilibria learning reinforcement learning simulations