Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
This paper presents a methodology for automatically generating online scheduling strategies for a complex objective defined by a machine provider. To this end, we assume independe...
Carsten Franke, Frank Hoffmann, Joachim Lepping, U...
Recent research showed that the majority of compatibility-breaking changes in a component-based, object-oriented software system are refactorings [5]. The software updating proces...
Abstract. This paper presents parallel approaches to the complete transient numerical analysis of stochastic reward nets (SRNs) for both shared and distributed-memory machines. Par...
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...