Robust Multi-agent Counterfactual Prediction

We consider the problem of using logged data to make predictions about what would happen if we changed the'rules of the game' in a multi-agent system. This task is difficult because in many cases we observe actions individuals take but not their private information or their full reward functions. In addition, agents are strategic, so when the rules change, they will also change their actions.