A Knowledge-Driven Approach to Dynamic Path Planning: Fuzzy A*-Based Method for Scalable Multi-Agent Systems

Path planning plays a pivotal role in the successful deployment of multi-agent systems. However, the adaptability and scalability of traditional path planning algorithms falter in dynamic, complex environments. This paper introduces the Fuzzy A* algorithm – an innovative path planning approach that combines the deterministic A* algorithm with the adaptability of fuzzy logic. The proposed algorithm modifies the cost and heuristic functions dynamically in response to local environmental variables, offering a more robust solution to the challenges faced in large-scale, dynamic environments. This paper explains the principles underpinning the Fuzzy A* algorithm and explores its potential in complex scenarios. Through benchmarking against traditional path planning algorithms, we underscore the superior adaptability, efficiency, and scalability of the proposed algorithm. The study presents this innovative algorithm as a promising future solution in path planning for scalable multi-agent systems.