A hierarchical task network planner for pathfinding in real-time strategy games

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, we propose an automatic mechanism of Hierarchical Task Networks (HTNs) creation for solving the problem of real-time path planning in Real-Time Strategy (RTS) Games. HTNs are created using an abstraction of the game map. A real-time heuristic search approach called Learning Real-Time A* (LRTA) is applied to execute the primitive tasks of the HTNs. The main purpose of using a HTN based real-time path planner is to restrict the real-time search to a shorter part of the problem space while keeping it in the direction of the actual goal position. Results show that the hierarchical approach reduces the suboptimality of the LRTA and speeds up the convergence process.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Symposium on AI and Games - A Symposium at the AISB 2010 Convention
Pages1-7
Number of pages7
Publication statusPublished - 2010
Event3rd International Symposium on Artificial Intelligence and Games - A Symposium at the AISB 2010 Convention - Leicester, United Kingdom
Duration: 29 Mar 20101 Apr 2010
Conference number: 3

Conference

Conference3rd International Symposium on Artificial Intelligence and Games - A Symposium at the AISB 2010 Convention
CountryUnited Kingdom
CityLeicester
Period29/03/101/04/10

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  • Cite this

    Naveed, M., Kitchin, D., & Crampton, A. (2010). A hierarchical task network planner for pathfinding in real-time strategy games. In Proceedings of the 3rd International Symposium on AI and Games - A Symposium at the AISB 2010 Convention (pp. 1-7)