Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
We explore combining reinforcement learning with a hand-crafted local controller in a manner suggested by the chaotic control algorithm of Vincent, Schmitt and Vincent (1994). A c...
This paper proposes and evaluates a multi-objective evolutionary algorithm for survival analysis. One aim of survival analysis is the extraction of models from data that approxima...
Christian Setzkorn, Azzam Fouad George Taktak, Ber...
We consider the concepts of a t-total vertex cover and a t-total edge cover (t 1), which generalize the notions of a vertex cover and an edge cover, respectively. A t-total verte...
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...