Recent work in transfer learning has succeeded in making reinforcement learning algorithms more efficient by incorporating knowledge from previous tasks. However, such methods typ...
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
Representing agent policies compactly is essential for improving the scalability of multi-agent planning algorithms. In this paper, we focus on developing a pruning technique that...
Abstract. We present a method that improves the results of network intrusion detection by integration of several anomaly detection algorithms through trust and reputation models. O...
Filling operations are procedures which are used in Discrete Tomography for the reconstruction of lattice sets having some convexity constraints. In [1], an algorithm which perform...