Imitation Learning Methods

Inverse Q-Learning

Inverse Q-Learning (IQ-Learn) is a a simple, stable & data-efficient framework for Imitation Learning (IL), that directly learns soft Q-functions from expert data. IQ-Learn enables non-adverserial imitation learning, working on both offline and online IL settings. It is performant even with very sparse expert data, and scales to complex image-based environments, surpassing prior methods by more than 3x.

It is very simple to implement requiring ~15 lines of code on top of existing RL methods.

Source: IQ-Learn: Inverse soft Q-Learning for Imitation


Paper Code Results Date Stars


Task Papers Share
Imitation Learning 3 42.86%
Reinforcement Learning (RL) 1 14.29%
Atari Games 1 14.29%
Continuous Control 1 14.29%
Decision Making 1 14.29%


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign