Before revision:  By dynamically tuning the prior specified to the agents, we formulate an active IRL framework which enhances these detection tests and minimizes their Type-II and Type-I error probabilities of utility maximization detection.
After revision:  By dynamically tuning the prior specified to the agents, we formulate an IRL framework which enhances these detection tests and minimizes their Type-II and Type-I error probabilities of utility maximization detection.