# Linear conic optimization for inverse optimal control

arXiv: https://arxiv.org/abs/1412.2277 · HTML: https://mlsanity.com/paper/1412.2277/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Dec 2014.

## Built on by (most cited first, 2 of 2)

- [Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations](https://mlsanity.com/paper/2112.14004/) (2021)
- [Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces](https://mlsanity.com/paper/2405.15509/) (2024)

## Abstract (arXiv)

We address the inverse problem of Lagrangian identification based on trajecto-ries in the context of nonlinear optimal control. We propose a general formulation of the inverse problem based on occupation measures and complementarity in linear programming. The use of occupation measures in this context offers several advan-tages from the theoretical, numerical and statistical points of view. We propose an approximation procedure for which strong theoretical guarantees are available. Finally, the relevance of the method is illustrated on academic examples.