Control of Autonomous Multi-Agent Systems
|schedule||20 Feb - 27 May 2017 (6 credits)|
see websites for Part 1 and Part 2 for detailed schedule
|office hours||Delli Priscoli: send e-mail|
Oriolo: Thu 14:00-16:00, room A211, DIAG, Via Ariosto 25, Rome
| e-mail||dellipri [at] diag [dot] uniroma1 [dot] it|
oriolo [at] diag [dot] uniroma1 [dot] it
of the Master in Control Engineering (MCER) at Sapienza University of Rome.
course presents the basic methods for modeling, analyzing and
controlling multi-agent systems, with special emphasis on distributed
strategies. Applications will be presented in the control of
communication and electrical networks as well as of multi-robot
systems. The student will be able to analyze and design architectures,
algorithms, and modules for controlling multi-agent systems.
course is organized in 2 parts:
additional details and material, access the webpages
of the individual parts by following the above links.
1 (Francesco Delli Priscoli, Feb-Apr 2017): Examples of
multi-agent scenarios in the communication and energy networks.
Centralized vs. decentralized architectures. Multi-agent networks with
limited or no information exchanges among agents. Overview of learning
methodologies (in particular, Reinforcement Learning), game theory,
negotiation, auctions, Kalman filtering. Behavior of these
methodologies in distributed multi-agent frameworks (e.g., behavior of
Reinforcement Learning techniques in a distributed framework,
Distributed Kalman Filtering). Application to specific multi-agent
scenarios (e.g, Reinforcement Learning techniques for Quality of
Experience control, Distributed Kalman Filtering for sensor networks).
2 (Giuseppe Oriolo, Apr-May, 2017): Examples of applications of
multi-robot systems. Centralized vs. decentralized architectures.
Mathematical tools: Adjacency graph and matrix; Laplacian; Connectivity
and Consensus; Passivity and Lyapunov stability; Interconnection of
mechanical systems. Application to multi-UAV systems: Formation control
with time-varying topology; Formation control with connectivity
maintenance; Steady-state behaviors; Bearing-based formation control.
Application to multi-UGV systems: Cooperative Mobile Manipulations; Cooperative exploration of unknown
environments; Mutual localization with anonymous measurements; Target
localization and encircling.
obtain 6 credits for this course it is necessary to
complete separate activities for Parts 1 and 2. In particular, for each part the student must carry out a small project which typically requires reading some technical papers and performing some simulations. To register the final grade, sign-up via Infostud is required.
Questions/comments: oriolo [at] diag [dot] uniroma1 [dot] it