M. Mohri

Theoretical Foundations and Effective Algorithms for Policy-Aware Simulator Learning

This work proposes that the objective for learning simulators should be strategic robustness rather than predictive accuracy, and formulate this as a zero-sum minimax game between a model player and an adversarial policy player, which yields a provably convergent active data selection algorithm.