We study the notion of learning in an oblivious changing environment. Existing online learning algorithms which minimize regret are shown to converge to the average of all locally...
This paper addresses the problem of multiagent task allocation in extreme teams. An extreme team is composed by a large number of agents with overlapping functionality operating i...
We improve the resistance of gossip-based multicast to (Distributed) Denial of Service (DoS) attacks using dynamic local adaptations at each node. Each node estimates the current ...
In this paper, we propose the island model parallel memetic algorithm with diversity-based dynamic adaptive strategy (PMADLS) for controlling the local search frequency and demons...
—This paper presents a novel cross-layer design for joint power and end-to-end rate control optimization in DSCDMA wireless networks, along with a detailed implementation and eva...
Marco Belleschi, Lapo Balucanti, Pablo Soldati, Mi...