20 citations · 110 across the 17 of their papers we have counts for
6 papers · 1 filter
Submodular Multi-Agent Policy Learning for Online Distributed Task Allocation in Open Multi-Agent Systems
Jing Liu, Yangyang Yang, Luca Ballotta +3
This paper studies multi-agent reinforcement learning with submodular team utilities for online distributed task allocation. In this setting, each agent selects one action from a l…
VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning
Luca Ballotta, Nicolò Dal Fabbro, Giovanni Perin +3
Assisted and autonomous driving are rapidly gaining momentum and will soon become a reality. Artificial intelligence and machine learning are regarded as key enablers thanks to the…
Can Competition Outperform Collaboration? The Role of Misbehaving Agents
Luca Ballotta, Giacomo Como, Jeff S. Shamma +1
We investigate a novel approach to resilient distributed optimization with quadratic costs in a multi-agent system prone to unexpected events that make some agents misbehave. In co…
A Reinforcement Learning Approach to Sensing Design in Resource-Constrained Wireless Networked Control Systems
Luca Ballotta, Giovanni Peserico, Francesco Zanini
In this paper, we consider a wireless network of smart sensors (agents) that monitor a dynamical process and send measurements to a base station that performs global monitoring and…
Competition-Based Resilience in Distributed Quadratic Optimization
Luca Ballotta, Giacomo Como, Jeff S. Shamma +1
This paper proposes a novel approach to resilient distributed optimization with quadratic costs in a networked control system (e.g., wireless sensor network, power grid, robotic te…
Optimal Network Topology of Multi-Agent Systems subject to Computation and Communication Latency (with proofs)
Luca Ballotta, Mihailo R. Jovanović, Luca Schenato
We study minimum-variance feedback-control design for a networked control system with retarded dynamics, where inter-agent communication is subject to latency. We prove that such a…