3 accepted papers
Learning control policies has become an appealing alternative to the derivation of control laws based on classic control theory. Value iteration approaches have proven an outstanding flexibility, while maintaining high data efficiency when combined with probabilistic models to eliminate model bias.
Machine learning and deep learning in particular has advanced tremendously on perceptual tasks in recent years. However, it remains vulnerable against adversarial perturbations of the input that have been crafted specifically to fool the system while being quasi-imperceptible to a human. In this wo…
Learning control has become an appealing alternative to the derivation of control laws based on classic control theory. However, a major shortcoming of learning control is the lack of performance guarantees which prevents its application in many real-world scenarios. As a step in this direction, we…