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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Alessio Sacco

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Open access 2026

Online Reinforcement Learning From Existing Heuristics for TCP Congestion Control

Mutant, an online reinforcement learning algorithm for congestion control that adapts to the behavior of the best-performing schemes, outperforming them in most network conditions is proposed, making it robust under diverse and dynamic network conditions.

Lorenzo Pappone, Alessio Sacco, Flavio Esposito · 0 citations
Open access 2026

Adaptive SDN Autoscaling via Generalizable Multi-Agent Reinforcement Learning With EAGLE

This work proposes EAGLE, a Multi-Agent Reinforcement Learning (MARL) system that autonomously orchestrates the scaling of network resources to meet flow demands and reduce power consumption, and shows that the trained model can “zero-shot generalize” to unseen network topologies that share structural or statistical si...

Doriana Monaco, Alessio Sacco, Flavio Esposito et al. · 0 citations

Testing the Divergence Stack Memory on GPGPUs: A Modular in-Field Test Strategy

RL-ICE is proposed as an innovative scheduler that can work in such a cloud continuum by leveraging a multi-cluster and hierarchical RL to satisfy both user Quality of Experience (QoE) metrics and tenant’s costs.

Doriana Monaco, Alessio Sacco, C. Casetti et al. · 0 citations

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