Yassine BOUARGANE
Papers
1
Total Citations
8
H-Index
1
About
Yassine Bouargane is a researcher in artificial intelligence and path planning, with a focus on search algorithms and their practical applications in navigation systems. His most-cited work, "Exploring Maze Navigation: A Comparative Study of DFS, BFS, and A* Search Algorithms" (2024), has garnered 8 citations and provides a rigorous evaluation of three fundamental search strategies—Depth-First Search, Breadth-First Search, and A*—using Python and the Pmaze environment. By systematically comparing these algorithms on path cost and computational complexity, Bouargane offers valuable insights for researchers and engineers working on autonomous navigation, robotics, and game development. His study stands out for its clear methodology and practical relevance, helping practitioners select the most efficient algorithm for real-world maze-solving and path-planning tasks. Bouargane’s work contributes to the broader understanding of algorithmic trade-offs in AI, making his research a useful reference for students and professionals seeking to optimize navigation in constrained environments.
Research Focus
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Top Papers
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