The classical approach is to find the optimal reward function by inverse reinforcement learning (IRL) (Russell, 1998;Ng et al., 2000) to explain expert behaviors.
to encourage the agent to find more diverse evidential paths, it is desirable to train the agent by imitating each trajectory instead of each of its state-action pairs.