Imitation Learning

Imitation learning is a branch of machine learning where an artificial agent learns to perform tasks by observing and mimicking expert demonstrations rather than through trial and error. It is often used in robotics to teach complex behaviors, such as manipulation or locomotion, by replicating human or simulated actions. By learning from example data, imitation learning enables robots and AI systems to acquire skills more efficiently and safely, serving as a foundation for advanced control and decision-making in real-world environments.