Youssef Fathi
Université Moulay Ismail de Meknes, Instituto Superior da Maia
Papers
3
Total Citations
30
H-Index
3
About
Dr. Youssef Fathi is a leading researcher in autonomous robotics and multi-agent systems, with a focused expertise in intelligent path planning. His work masterfully integrates reinforcement learning, specifically collaborative Q-learning, with Holonic Multi-Agent Systems (H-MAS) to solve complex navigation problems for autonomous mobile robots. Dr. Fathi’s major contributions include pioneering a novel architecture where robots, acting as "head-holons," cooperate to learn optimal paths. He introduced a dual Q-table system—the Q-Master Table (QMT) and Q-Embedded Table (QET)—which allows for both collaborative global learning and efficient local execution. Further advancing the field, he has combined this collaborative learning with Fuzzy Inference Systems to handle environmental uncertainty. His foundational papers, including "Collaborative Q-learning path planning for autonomous robots based on holonic multi-agent system" and "H-MAS architecture and reinforcement learning method for autonomous robot path planning," have each garnered 12 citations, establishing a solid foundation for subsequent research in distributed, intelligent robotics. Dr. Fathi’s work provides a critical framework for creating more adaptive and efficient autonomous systems.
Research Focus
Key Achievements
Top Papers
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