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About

Carlos Delgado-Mata is a researcher whose work sits at the intersection of robotics, artificial intelligence, and interactive entertainment. His primary research areas include ethology-inspired robotics, adaptive game mechanics, and personalised interactive storytelling. Delgado-Mata’s most cited paper, “A Differential-Drive Mobile Robot Driven by an Ethology Inspired Behaviour Architecture” (2012, 16 citations), introduces a novel action selection mechanism for mobile robots, drawing inspiration from animal behaviour to enhance autonomous decision-making in security and reconnaissance applications. He has also made notable contributions to adaptive video games, as seen in his work on “Adaptive Physics for Game-Balancing in Video-Games for Social Interaction” (2011, 6 citations), where he developed a system that dynamically adjusts game physics to match player skill levels, improving social play. His exploration of behavioural reactive agents to define personality traits in video games, such as in “Überpong” (2008, 4 citations), demonstrates a sustained interest in creating more engaging and human-like AI opponents. Additionally, Delgado-Mata’s work on the MPISTE project (2010, 3 citations) pioneers location-based interactive storytelling on mobile devices, blending narrative with physical context. With a cumulative citation count of over 30, his research continues to influence the design of intelligent, adaptive systems that bridge the gap between virtual and physical worlds.