We review the idea that Theory of Mind—our ability to reason about other people's mental
states—can be formalized as inverse reinforcement learning. Under this framework,
expectations about how mental states produce behavior are captured in a reinforcement
learning (RL) model. Predicting other people's actions is achieved by simulating a RL model
with the hypothesized beliefs and desires, while mental-state inference is achieved by
inverting this model. Although many advances in inverse reinforcement learning (IRL) did …