Improved Heuristics for Optimal Pathfinding on Game Maps

Author:

Björnsson Yngvi,Halldórsson Kári

Abstract

As computer game worlds get more elaborate the more visible pathfinding performance bottlenecks become. The heuristic functions typically used for guiding A*-based path inding are too simplistic to provide the search with the necessary guidance in such large and complex game worlds. This may result in A*-search exploring the entire game map in order to find a path between two distant locations. This article presents two effective heuristics for estimating distances between locations in large and complex game maps. The former, the dead-end heuristic, eliminates from the search map areas that are provably irrele- vant for the current query, whereas the second heuristic uses so-called gateways to improve its estimates. Empirical evaluation on actual game maps shows that both heuristics reduce the exploration and time complexity of A* search significantly over a standard octile distance metric.

Publisher

Association for the Advancement of Artificial Intelligence (AAAI)

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. LuckyMera: a modular AI framework for building hybrid NetHack agents;Intelligenza Artificiale;2024-05-29

2. Game-map Pathfinding with Per-Problem Selection of Synthesized Heuristics;2023 IEEE Conference on Games (CoG);2023-08-21

3. Research of the Path Finding Algorithm A* in Video Games;Highlights in Science, Engineering and Technology;2023-04-01

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