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Michael Georgeff is a pioneering figure in artificial intelligence, best known for his foundational contributions to autonomous agent architectures, rational agency, and real-time reasoning systems. His research established the theoretical and practical groundwork for building AI systems capable of operating in dynamic, continuously changing environments. Georgeff's most influential work centers on the Procedural Reasoning System (PRS), a landmark architecture that models agents through the psychological attitudes of belief, desire, and intention — a framework now central to AI agent theory. His 1987 paper on reactive reasoning and planning for autonomous mobile robots has accumulated 881 citations, reflecting its enduring influence on robotics and intelligent systems design. His subsequent development of PRS as a generic real-time reasoning platform, attracting nearly 400 citations, demonstrated the architecture's versatility across applications ranging from mobile robots to air traffic management and surveillance aircraft control. Beyond agent architectures, Georgeff made notable contributions to the formal representation of procedural knowledge, proposing declarative semantics for process-based reasoning that helped bridge commonsense knowledge and computational implementation. His early work on AI-based automation for NASA space stations further illustrates the applied ambition of his research. With well over 1,900 combined citations, Georgeff's work remains essential reading for researchers in multiagent systems, autonomous robotics, and cognitive architectures.