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About

Don Perlis is a pioneering researcher in artificial intelligence, with a career-long focus on metacognition, commonsense reasoning, and the development of autonomous robotic agents. His work bridges the gap between symbolic AI and machine learning, exploring how robots can learn and reason about their own cognitive processes. Perlis’s foundational essay collection, *Some Brief Essays on Mind* (1989, 36 citations), laid the groundwork for his exploration of consciousness and reasoning in machines. He is perhaps best known for his visionary "Robot Baby" project, introduced in papers such as *Seven Days in the Life of a Robotic Agent* (2003, 20 citations) and *The Robot Baby and Massive Metacognition* (2012, 9 citations). This long-term initiative proposes that robots, like human infants, can develop intelligence through continuous interaction with their environment, leveraging metacognition to synergize learning and reasoning. Perlis has also contributed to reinforcement learning for robotics, as seen in *From Robots to Reinforcement Learning* (2013, 6 citations). His work challenges traditional AI boundaries, advocating for machines that not only act but also reflect on their own internal reasoning—a concept that continues to inspire researchers in cognitive robotics and artificial general intelligence.