Скачать или смотреть Introduction to Imitation Learning.

A brief overview of imitation learning by SCLab. Imitation learning is a machine learning approach where an agent learns a task by observing and mimicking expert demonstrations, similar to how humans learn a new skill by watching others. It is often framed as a supervised learning problem, where the agent's goal is to learn a policy (a strategy for choosing actions) that replicates the expert's behavior. Key techniques include Behavioral Cloning (BC), which directly learns to map states to actions from expert data, and Inverse Reinforcement Learning (IRL), which infers the underlying reward function the expert was optimizing.

Presented by Md Mahin, PhD, MD Anderson Cancer Center, Texas, USA.
You can follow his YouTube channel for advanced AI (   / @simplemahin  )
Hosted by SCLab, Inje University, Republic of Korea.