Kernel Density Bayesian Inverse Reinforcement Learning

Understand

Inverse reinforcement learning (IRL) methods infer an agent's reward function using demonstrations of expert behavior.

• A Bayesian IRL approach models a distribution over candidate reward functions, capturing a degree of uncertainty in the inferred reward function.
• This is critical in some applications, such as those involving clinical data.
• Typically, Bayesian IRL algorithms require large demonstration datasets, which may not be available in practice.