Learning for Control: An Inverse Optimization Approach

Data driven learning has become a common practice in many decision making applications. Machine learning techniques are the dominant methods employed but have limitations with respect to constraints satisfaction. A learning method is presented to learn the mapping from an input space to an action space, which is particularly suitable when the...