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

Munir Naveed; Diane Kitchin; Andrew Crampton

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

Munir Naveed, Diane Kitchin, Andrew Crampton

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 language	English
Title of host publication	Proceedings of the 3rd International Symposium on AI and Games - A Symposium at the AISB 2010 Convention
Pages	1-7
Number of pages	7
Publication status	Published - 2010
Event	3rd International Symposium on Artificial Intelligence and Games - A Symposium at the AISB 2010 Convention - Leicester, United Kingdom Duration: 29 Mar 2010 → 1 Apr 2010 Conference number: 3

Conference

Conference	3rd International Symposium on Artificial Intelligence and Games - A Symposium at the AISB 2010 Convention
Country/Territory	United Kingdom
City	Leicester
Period	29/03/10 → 1/04/10

Cite this

@inproceedings{ee9d600d93124bcf8e2a35ed952e0070,

title = "A hierarchical task network planner for pathfinding in real-time strategy games",

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.",

author = "Munir Naveed and Diane Kitchin and Andrew Crampton",

year = "2010",

language = "English",

isbn = "1902956907",

pages = "1--7",

booktitle = "Proceedings of the 3rd International Symposium on AI and Games - A Symposium at the AISB 2010 Convention",

note = "3rd International Symposium on Artificial Intelligence and Games - A Symposium at the AISB 2010 Convention ; Conference date: 29-03-2010 Through 01-04-2010",

}

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, 3rd International Symposium on Artificial Intelligence and Games - A Symposium at the AISB 2010 Convention, Leicester, United Kingdom, 29/03/10.

TY - GEN

T1 - A hierarchical task network planner for pathfinding in real-time strategy games

AU - Naveed, Munir

AU - Kitchin, Diane

AU - Crampton, Andrew

N1 - Conference code: 3

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84863008511&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84863008511

SN - 1902956907

SN - 9781902956909

SP - 1

EP - 7

BT - Proceedings of the 3rd International Symposium on AI and Games - A Symposium at the AISB 2010 Convention

T2 - 3rd International Symposium on Artificial Intelligence and Games - A Symposium at the AISB 2010 Convention

Y2 - 29 March 2010 through 1 April 2010

ER -

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

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