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About

Paulo E. Santos is a researcher whose work bridges artificial intelligence, robotics, and cognitive reasoning, with particular expertise in qualitative spatial reasoning, case-based reasoning, and reinforcement learning. His research has made significant contributions to how autonomous robots perceive, interpret, and reason about their environments — from hypothesising spatial object relations from sensor data (2002) to developing sophisticated logic-based frameworks for interpreting visual scene sequences (2003). Santos has been especially influential in combining case-based reasoning with machine learning techniques. His most-cited work, "Transferring knowledge as heuristics in reinforcement learning: A case-based approach" (2015, 67 citations), pioneered methods for accelerating agent learning through knowledge transfer — a contribution extended in subsequent publications accumulating over 135 citations across related works. His investigations into shadow-based robot localisation represent a uniquely creative strand of research, drawing on cognitive psychology to enhance robotic spatial awareness. More recently, Santos has expanded into emotion recognition for assistive robotics (2023), reflecting a commitment to human-robot interaction. His career demonstrates a consistent and inventive effort to endow robots with richer, more human-like reasoning capabilities, making his body of work essential reading for researchers in AI, cognitive robotics, and autonomous systems.