Ayoub HSAINE
Papers
1
Total Citations
8
H-Index
1
About
Ayoub Hsaine is an emerging researcher in artificial intelligence and algorithmic optimization, with a primary focus on path planning and search algorithm efficiency. His most cited work, "Exploring Maze Navigation: A Comparative Study of DFS, BFS, and A* Search Algorithms" (2024, 8 citations), provides a rigorous comparative analysis of depth-first search, breadth-first search, and A* algorithms using Python and the Pmaze environment. This study systematically evaluates algorithmic performance in terms of path cost and computational complexity, offering practical insights for robotics, autonomous navigation, and game development. Despite being early in his career, Hsaine’s work demonstrates a strong commitment to bridging theoretical computer science with real-world applications. His research contributes to foundational knowledge in heuristic search and decision-making under constraints, making it valuable for students and researchers exploring efficient pathfinding solutions. As his citation count grows, Hsaine is establishing himself as a thoughtful contributor to AI-driven optimization, with potential for future impact in intelligent systems and autonomous agent design.
Research Focus
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Top Papers
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