  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.
