— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
Axel Rottmann, Christian Plagemann, Peter Hilgers,...
In this work, we propose two high-level formalisms, Markov Decision Petri Nets (MDPNs) and Markov Decision Well-formed Nets (MDWNs), useful for the modeling and analysis of distrib...
Marco Beccuti, Giuliana Franceschinis, Serge Hadda...
The substitution of ATM transport by IP in future UMTS Radio Access Networks (UTRAN) introduces several performance challenges that need to be addressed to guarantee the feasibili...
This paper investigates the pre-conditions for successful combination of document representations formed from structural markup for the task of known-item search. As this task is ...
Commercial OLAP systems usually treat OLAP dimensions as static entities. In practice, dimension updates are often necessary in order to adapt the multidimensional database to chan...