Methods › Reinforcement Learning › Imitation Learning Methods › IQ-Learn

Inverse Q-Learning

IQ-Learn

4 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

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

Papers archive 2025-07-28

4 shown of 4, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

On Learning Informative Trajectory Embeddings for Imitation, Classification and Regression
16 Jan 2025 · 1 repository · arXiv:2501.09327
Adversarial Imitation Learning via Boosting
12 Apr 2024 · 0 repositories · arXiv:2404.08513
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees
4 Oct 2022 · 0 repositories · arXiv:2210.01808
IQ-Learn: Inverse soft-Q Learning for Imitation
23 Jun 2021 · 5 repositories · arXiv:2106.12142

Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)

Tasks archive 2025-07-28

16 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

Task	Papers
Imitation Learning	3
Decision Making	2
Sequential Decision Making	2
Atari Games	1
Autonomous Driving	1
Clustering	1
Continuous Control	1
MuJoCo	1
MuJoCo Games	1
Q-Learning	1
Reinforcement Learning	1
Reinforcement Learning (RL)	1
Self-Driving Cars	1
counterfactual	1
regression	1
reinforcement-learning	1

Usage over time archive 2025-07-28

Papers per year the archive tags with this method, by the paper's archive date (4 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Imitation Learning Methods

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