Jean-Yves Donnart

Papers

Total Citations

126

H-Index

About

Jean-Yves Donnart is a pioneering researcher in artificial life and cognitive robotics, best known for his foundational work on motivationally autonomous animats. His key research areas include hierarchical learning systems, spatial navigation, and adaptive behavior in artificial agents. Donnart’s most influential contribution is the development of MonaLysa, a control architecture that integrates reactive and planning rules through a hierarchical classifier system. This system enables an animat to autonomously select actions and goals based on its internal state, environmental stimuli, and physiological needs—a breakthrough in creating agents that exhibit genuine motivational autonomy. His seminal 1996 paper on this topic has garnered 107 citations, reflecting its lasting impact on the field. Donnart also advanced spatial cognition with his work on MonaLysa’s route-following navigation strategy, demonstrating robust map building and self-positioning even under noisy conditions (17 citations). His doctoral thesis (1998) further synthesized these contributions, cementing his reputation as a key figure in adaptive agent architectures. Donnart’s work remains essential reading for researchers exploring autonomous decision-making, learning, and spatial reasoning in artificial systems.