Ho-Sik Seok

Papers

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About

Ho-Sik Seok is a pioneering researcher in the field of evolvable hardware (EHW) and autonomous robotics, with a focus on enabling machines to adapt and learn in real-time. His core contributions lie at the intersection of genetic programming (GP) and hardware design, where he has developed innovative strategies for online adaptive learning. Seok’s seminal 2002 work, “Behavior evolution of autonomous mobile robot using genetic programming based on evolvable hardware,” introduced a novel GP-based evolutionary method that leverages tree-structured chromosomes to control EHW, allowing robots to evolve behaviors autonomously. This foundational paper has garnered 9 citations, establishing a key methodology for adaptive systems. In his subsequent studies, Seok addressed critical challenges in EHW, such as process decomposition (6 citations) and sensor calibration (3 citations), proposing GP-driven strategies to partition complex tasks and correct sensor noise for more reliable autonomous navigation. His research demonstrates how evolvable hardware can bridge the gap between general-purpose processors and ASICs, offering both flexibility and performance. Seok’s work remains influential for students and researchers exploring adaptive robotics, evolutionary computation, and hardware-software co-design, providing a blueprint for building robust, self-improving systems in dynamic environments.