Kourosh Nafasi

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Kourosh Nafasi is a pioneer in evolutionary robotics, a field that uses principles of natural selection to design intelligent machine behavior. His most influential work, "Selection for Wandering Behavior in a Small Robot" (1994), which has garnered a combined 62 citations, stands as a landmark study in embodied artificial intelligence. In this research, Nafasi evolved artificial neural networks to control simple Lego™ robots, tasking them with a deceptively complex goal: to touch as many squares on a grid as possible within a fixed time. By successfully transferring evolved controllers from simulation to physical robots, he demonstrated that complex, adaptive behaviors like exploration and wandering could emerge not from explicit programming, but from a Darwinian process of selection and mutation. This foundational work bridged the gap between theoretical evolution and real-world robotics, proving that even minimal hardware could exhibit surprisingly sophisticated, goal-driven movement. Nafasi’s contributions remain a cornerstone for researchers in autonomous robotics and artificial life, illustrating how simple evolutionary pressures can yield robust, intelligent behavior in machines.