IQ-Learn

2000년 도입 · 논문 4편에서 사용

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. <span class="description-source">Source: IQ-Learn: Inverse soft Q-Learning for Imitation</span>