Mini toolsDefinition
A method for learning reward functions from expert demonstrations rather than explicit rewards.
Detailed Explanation
IRL aims to recover the underlying reward function that an expert is optimizing based on observed optimal behavior. This is useful when it's easier to demonstrate desired behavior than to specify a reward function. It can help learn complex behaviors and preferences from human demonstrations.
Use Cases
Learning from human demonstrations, autonomous driving, robot imitation learning, behavior modeling
