Parte I
Examples of multi-agent scenarios in communication, energy, transport, health networks/systems derived from research projects funded by the European Union. Comparison between centralized and distributed architectures. Extension of the methodologies (especially machine learning, reinforcement learning, model predictive control) and problems (concerning the control of communication, energy, transport and health networks/systems, as well as the security of such networks/systems) studied in the context of previous courses (in particular, Control of Communication and Energy Network) to the multi-agent context.
Parte II
Held by prof. Andrea Cristofaro
Testi consigliati:
Dispense e articoli derivanti dai Deliverables prodotti nell'ambito dei progetti di ricerca della UE (in particolare, progetti FP8 BONVOYAGE, FP8 ATENA, Artemis pSHIELD/nSHIELD).
I. Goodfellow, Y. Bengio, A. Courville, "Deep Learning", MIT Press, 2016.
M. Vidal, “Fundamentals of Multiagent Systems,” 2011.
M. Mesbahi and M. Egerstedt, “Graph Theoretic Methods in Multiagent Systems,” Princeton University Press, 2010.
- Teacher: EMANUELE De Santis
- Teacher: Francesco DELLI PRISCOLI
- Teacher: Roberto Germanà
- Teacher: Alessandro Giuseppi
- Teacher: FRANCESCO LIBERATI