Essam Debie

University of Canberra, Australian Defence Force Academy

Papers

Total Citations

H-Index

About

Essam Debie is a leading researcher in swarm robotics and multi-agent systems, whose work bridges bio-inspired coordination and machine learning. His most-cited paper, "Swarm Robotics: A Survey from a Multi-Tasking Perspective" (2023, 50 citations), provides a comprehensive analysis of how social insect behaviors—like those of bees and ants—inform robot cooperation through communication, coordination, and collaboration, enabling faster task completion in complex environments. This survey has become a key reference for researchers exploring multi-tasking in robotic swarms. Debie also introduced Swarm Q-Learning (SQL), a tabular multi-agent reinforcement learning algorithm for formation control, and enhanced it with knowledge sharing across environments (2018, 11 citations), advancing how agents maintain geometric shapes over time. Earlier, he explored the evolution of intrinsic motives in multi-agent simulations (2012, 10 citations), contributing to foundational understanding of autonomous motivation in artificial systems. With a career spanning over a decade, Debie’s work has shaped both theoretical frameworks and practical applications in swarm intelligence, making him a notable figure for students and researchers interested in decentralized coordination and adaptive learning.