Gabriel Garcez Barros Sousa

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About

Gabriel Garcez Barros Sousa is a researcher focused on multi-agent systems and coordinated robotics, with a particular emphasis on robotic soccer. His key research areas include setplay generation, learning from demonstration (LfD), and strategic planning for multi-robot teams. Sousa's major contributions center on the development and enhancement of the Strategy Planner (SPlanner) and the FCPortugal Setplays Framework (FSF), tools that enable the design of sophisticated, coordinated strategic plans for robotic soccer teams. Notably, his work on generating datasets for learning setplays from demonstration (2021) and enhancing defense and pass strategies within an LfD approach (2020) has each garnered 5 citations, demonstrating steady impact in this niche field. These contributions advance the state of the art in multi-agent coordination, moving beyond hand-coded plans toward data-driven, adaptive strategies. Sousa's research is particularly relevant for students and researchers working in multi-robot systems, collective sports robotics, and automated strategic planning, offering practical toolkits that bridge the gap between human-designed plays and machine-learned coordination.