Reinforcement Learning · advanced · concept 190 of 311 · Updated Nov 4, 2026
Imitation Learning
Imitation learning teaches a system by showing it examples of an expert doing the task rather than defining a reward. It is often the fastest route to a working robot skill. The classic weakness is drift: once the system strays from what it saw, it has no idea how to recover, so newer methods keep collecting corrections from the expert.
Top AI contributors on this
- Stuart RussellUC Berkeley
- Pieter AbbeelAmazon / UC Berkeley
- Sebastian ThrunStanford University (adjunct)
- Lex FridmanMIT / Lex Fridman Podcast
- Sergey LevineUC Berkeley / Physical Intelligence
- Chelsea FinnStanford University / Physical Intelligence
Key terms
Behavior cloningDistribution shiftDAggerDemonstrationsInverse RL
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Where you meet it in the real world
Robot manipulation, driving, teaching agents from recorded human workflows
Guides and articles
CS 285: Deep Reinforcement Learning ↗
UC Berkeley
A Reduction of Imitation Learning (DAgger) ↗
Ross and others
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