32,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in über 4 Wochen
payback
16 °P sammeln
  • Broschiertes Buch

The characteristics of the future space missions are moving into areas where significant advantages would be gained from the development of an increasing level of autonomy distributed across the space systems. The Multi-Agent approach is an effective way to cope with this perspective: every space system is provided with computing capabilities implementing an intelligent behavior in terms of coordinated decision making. This book explores the benefits of a coordination strategy based on the temporal interdependence decoupling: every space system introduces local constraints in order to make…mehr

Produktbeschreibung
The characteristics of the future space missions are moving into areas where significant advantages would be gained from the development of an increasing level of autonomy distributed across the space systems. The Multi-Agent approach is an effective way to cope with this perspective: every space system is provided with computing capabilities implementing an intelligent behavior in terms of coordinated decision making. This book explores the benefits of a coordination strategy based on the temporal interdependence decoupling: every space system introduces local constraints in order to make redundant the coordination constraints. Therefore the interdependencies can be removed decomposing the global problem in local independent subproblems that implicitly satisfy the coordination requirements. This coordination strategy has the potential benefit of reducing the communication overhead, which becomes fundamental in space as the probability of communication failure and latency can seriously compromise the operations. This book should be especially useful to professionals in Space Operations or anyone else who is interested in distributed robotics systems.
Autorenporträt
Andrea Brambilla, Ph.D.: received his Doctoral Degree in Aerospace Engineering at the Politecnico di Milano in 2009. His research interests focus on Artificial Intelligence with an emphasis on Multi-Agent systems. In particular, he studied Multi-Agent planning and scheduling for real-time applications in dynamic and uncertain environments.