A model predictive controller 81 receives at least one of observations and state measurements from a control target and calculates control actions and generates trajectories based on an objective function and a set of constraints. An inverse model predictive control learner 82 compares features extracted from the trajectories of the control target generated by the model predictive controller 81 with features of data representing expert demonstrations and, by applying machine learning techniques, solves an optimization problem to update the objective function and constraints based on difference of compared features.
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