Learning foreign exchange intervention policies with an artificial market

We propose a multi-agent system which learns intervention policies and evaluates the effect of interventions in an artificial foreign exchange market. We introduce an intervention agent that has the role of the central bank to stabilize the market. We could show that the agent learned the effective intervention policies through the reinforcement learning.