HA Mallot

Papers

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About

Hanspeter A. Mallot is a leading figure in computational neuroscience and cognitive robotics, best known for pioneering work on spatial cognition and visual navigation. His research bridges biological vision and artificial systems, exploring how agents—both human and robotic—build internal representations of space. Mallot’s most cited paper, "View-based cognitive map learning by an autonomous robot" (1995, 21 citations), introduced a groundbreaking view-graph approach to map learning and navigation in mazes. Using graph theory, he demonstrated that a view-graph is a sufficient representation for complex map behaviors like path planning, and developed a neural network for unsupervised learning of these graphs from sequences of views. This work laid the foundation for modern view-based SLAM (Simultaneous Localization and Mapping) and remains influential in robotics and cognitive science. Mallot’s contributions extend to the study of optic flow, depth perception, and the neural basis of spatial memory, earning him recognition as a key thinker in how brains and machines navigate the world. His interdisciplinary approach continues to inspire students and researchers at the intersection of vision, learning, and autonomous behavior.