Paulo Eduardo Ubaldino de Souza

Institut Superieur de l'Aeronautique et de l'Espace (ISAE-SUPAERO), Université Fédérale de Toulouse Midi-Pyrénées

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About

Paulo Eduardo Ubaldino de Souza investigates the intersection of human cognition and autonomous robotics, focusing on how human-robot teams can make optimal decisions under uncertainty. His research integrates sequential decision-making, game theory, and cognitive science to design mixed-initiative systems where robots and human operators collaborate effectively. Souza’s most cited work (15 citations) introduces a Mixed-Observability Markov Decision Process (MOMDP) framework for target search missions that explicitly models the operator’s cognitive state, enabling robots to adapt their actions based on human attention and workload. He has also experimentally demonstrated how cognitive biases like the framing effect influence operator decisions in unmanned vehicle control (9 citations), and applied prospect theory to predict human choices in cooperative missions (5 citations). Beyond human-robot interaction, Souza has formulated decentralized game-theoretic approaches for multi-agent surveillance, minimizing idleness in aerial robot teams (4 citations). His work bridges artificial intelligence and behavioral economics, providing foundational methods for designing robots that understand and compensate for human cognitive limitations—critical for applications in search-and-rescue, surveillance, and autonomous systems where human oversight remains essential.