Inverse reinforcement learning (IRL) is a powerful framework to extract the reward function of an agent by observing its behavior, but IRL algorithms that infer point estimates can be misleading. A Bayesian approach to IRL can model a distribution …

Inverse reinforcement learning (IRL) methods attempt to recover the reward function of an agent by observing its behavior. Given the large amount of uncertainty in the underlying reward function, it is often useful to model this function …

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