Antti Keurulainen

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About

Antti Keurulainen is a researcher whose work bridges cognitive science and artificial intelligence, with a primary focus on understanding how intelligent agents perceive and learn action possibilities from their environments. His key research areas include affordance theory, reinforcement learning, and human-computer interaction. Keurulainen’s most notable contribution is his 2022 paper, “Rediscovering Affordance: A Reinforcement Learning Perspective,” which has garnered 21 citations. In this work, he addresses a critical gap in affordance theory—the lack of a mechanistic explanation for how affordances are discovered and adapted through interaction. By proposing an integrative framework that combines reinforcement learning principles with ecological psychology, Keurulainen offers a novel computational account of affordance-formation, providing a foundation for designing more intuitive and adaptive interactive systems. His work has significant implications for robotics, AI, and user interface design, suggesting that agents can learn to perceive action possibilities through trial-and-error experience. Keurulainen’s research is essential reading for students and researchers interested in the intersection of perception, action, and machine learning, as it provides a rigorous, testable model for one of the most fundamental concepts in cognitive science.