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 address a class of problems where decisions have to be optimized over a time horizon given that the future is uncertain and that the optimization decisions influence the time o...
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
We apply the NSGA-II algorithm and its controlled elitist version NSGA-IIc for the intensity modulated beam radiotherapy dose optimization problem. We compare the performance of th...
Michael Lahanas, Eduard Schreibmann, Natasa Milick...