20 papers
From Passive Mirrors to Active Agents: Holonic Digital Twins for Physical AI over Networks
Christo Kurisummoottil Thomas, Omar Hashash, Walid Saad
Despite advances in artificial intelligence (AI) across multiple sectors, today's AI tools, including deep learning and generative AI, still fail when embedded into physical system…
Compositional Semantic Communication for Physical AI: Category Theory Meets Game Theory
Christo Kurisummoottil Thomas, Walid Saad, Emilio Calvanese Strinati
Physical artificial intelligence (AI) systems involve distributed sensing agents with embedded AI models that must coordinate to perceive, reason, and act in networked environments…
Active Inference as the Test-Time Scaling Law for Physical AI Agents
Omar Hashash, Christo Kurisummoottil Thomas, Walid Saad +3
In this paper, a novel test-time scaling law for physical artificial intelligence (AI) agents is introduced. This scaling law enables physical AI agents to reason with their world…
Disentanglement with Holographic Reduced Representations
Jhonny J. Velasquez Olivera, Christo K. Thomas, Walid Saad
Disentanglement, the separation of factors of variation in data using neural networks, remains a long-standing challenge in machine learning. Prior work has addressed this problem…
Dynamic Hypergame for Task Assignment in Multi-platform Mobile Crowdsensing Under Incomplete Information
Sumedh J. Dongare, Christo Kurisummoottil Thomas, Andrea Ortiz +2
Mobile crowdsensing (MCS) is a promising distributed sensing paradigm for future wireless networks, where MCS platforms (MCSPs) recruit mobile units (MUs) through monetary incentiv…
Toward World Models for Epidemiology
Zeeshan Memon, Yiqi Su, Christo Kurisummoottil Thomas +3
World models have emerged as a unifying paradigm for learning latent dynamics, simulating counterfactual futures, and supporting planning under uncertainty. In this paper, we argue…