This paper studies how external incentives can help agents to coordinate in summary-statistic games. Agents follow a myopic best-reply rule and face a trade-off between efficiency and strategic uncertainty. A principal can help agents to coordinate on the Pareto optimal equilibrium by monitoring...

In traditional Reinforcement Learning (RL), agents learn to optimize actions in a dynamic context based on recursive estimation of expected values. We show that this form of machine learning fails when rewards (returns) are affected by tail risk, i.e., leptokurtosis. Here, we adapt a recent...