mlsanityData to 7 Oct 2026

A proof of convergence of inverse reinforcement learning for multi-objective optimization

arXiv 2305.06137 ↗First posted 10 May 2023cs.LG cs.AI stat.MLcited by 3

On the map: Offline RL and imitation learning from data → Inverse reinforcement learning

Abstract (arXiv)

We show the convergence of Wasserstein inverse reinforcement learning for multi-objective optimizations with the projective subgradient method by formulating an inverse problem of the multi-objective optimization problem. In addition, we prove convergence of inverse reinforcement learning (maximum entropy inverse reinforcement learning, guided cost learning) with gradient descent and the projective subgradient method.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Inverse reinforcement learning, one of 13 directions in Offline RL and imitation learning from data. Builds on 6 of its 22 references that are in the map. First posted on arXiv 10 May 2023.

Builds on

6 of 22 references.

References · 6

  1. 2016Generative Adversarial Imitation Learningcited by 1,576
  2. 2018Which Training Methods for GANs do actually Converge?cited by 672
  3. 2016Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimizationcited by 400
  4. 2023Handbook of Convergence Theorems for (Stochastic) Gradient Methodscited by 158
  5. 2013Projection onto the probability simplex: An efficient algorithm with a simple proof, and an applicationcited by 65
  6. 2018An Online-Learning Approach to Inverse Optimizationcited by 16

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 1.

3 papers.

  1. 2024Exact Solution to Data-Driven Inverse Optimization of MILPs in Finite Time via Gradient-Based Methodscited by 3
  2. 2025Inverse Mixed-Integer Programming: Learning Constraints then Objective Functionscited by 2
  3. 2026Explicit Iteration Complexity of Exact Data-Driven Inverse Optimization for Integer Linear Programscited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2023A proof of imitation of Wasserstein inverse reinforcement learning for multi-objective optimization
  2. 2024Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm
  3. 2020Regularized Inverse Reinforcement Learning
  4. 2025Statistical analysis of Inverse Entropy-regularized Reinforcement Learning
  5. 2025Learning Pareto-Optimal Rewards from Noisy Preferences: A Framework for Multi-Objective Inverse Reinforcement Learning
  6. 2026Maximum Entropy Inverse Reinforcement Learning for Mean-Field Games with Average Reward
  7. 2019On the Correctness and Sample Complexity of Inverse Reinforcement Learning
  8. 2023Inverse Reinforcement Learning With Constraint Recovery