Biased Cost Pathfinding


  • Alborz Geramifard University of Alberta
  • Pirooz Chubak University of Alberta
  • Vadim Bulitko University of Alberta



In this paper we introduce the Biased Cost Pathfinding (BCP) algorithm as a simple yet effective meta-algorithm that can be fused with any single-agent search method in order to make it usable in multi-agent environments. In particular, we focus on pathfinding problems common in real-time strategy games where units can have different functions and mission priorities. We evaluate BCP paired with the A* algorithm in several game-like scenarios. Performance improvement of up to 90% is demonstrated with respect to several metrics.




How to Cite

Geramifard, A., Chubak, P., & Bulitko, V. (2021). Biased Cost Pathfinding. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2(1), 112-114.