Mikhail Balabanov
Papers
1
Total Citations
2
H-Index
1
About
Mikhail Balabanov is a researcher in artificial intelligence and pathfinding algorithms, with a focus on optimizing navigation in uniform-cost grid environments. His most notable contribution is the modification of the JPS+ (Jump Point Search Plus) algorithm, a widely used technique for accelerating pathfinding in domains such as computer games, robotics, and road map navigation. In his 2018 paper, Balabanov proposed integrating a visibility graph into the map pre-processing logic, which significantly reduces pathfinding time by streamlining the algorithm’s search process. Although his work has garnered modest citation counts—his key paper has been cited twice—it represents a thoughtful refinement of an established method, offering practical improvements for real-time applications. Balabanov’s research bridges theoretical algorithm design and applied computational efficiency, making his contributions valuable for developers and researchers seeking faster, more reliable pathfinding solutions. His work underscores the importance of incremental innovation in algorithm optimization, demonstrating how targeted modifications can enhance performance in resource-constrained systems.
Research Focus
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Top Papers
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