Preprint Article Version 1 This version is not peer-reviewed

Modified Adversarial Hierarchical Task Network Planning in Real-Time Strategy Games

Version 1 : Received: 18 April 2017 / Approved: 19 April 2017 / Online: 19 April 2017 (04:41:22 CEST)

How to cite: Sun, L.; Jiao, P.; Xu, K.; Yin, Q.; Zha, Y. Modified Adversarial Hierarchical Task Network Planning in Real-Time Strategy Games. Preprints 2017, 2017040119 (doi: 10.20944/preprints201704.0119.v1). Sun, L.; Jiao, P.; Xu, K.; Yin, Q.; Zha, Y. Modified Adversarial Hierarchical Task Network Planning in Real-Time Strategy Games. Preprints 2017, 2017040119 (doi: 10.20944/preprints201704.0119.v1).

Abstract

Real-time strategy (RTS) game has proposed many challenges for AI research for its large state spaces, enormous branch factors, limited decision time and dynamic adversarial environment. To tackle above problems, the method called Adversarial Hierarchical Task Network planning (AHTN) has been proposed and achieves favorable performance. However, the HTN description it used cannot express complex relationships among tasks and impacts of environment on tasks. Moreover, the AHTN cannot handle task failures during plan execution. In this paper, we propose a modified AHTN planning algorithm named AHTNR. The algorithm introduces three elements essential task, phase and exit condition to extend the HTN description. To deal with possible task failures, the AHTNR first uses the extended HTN description to identify failed tasks. And then a novel task repair strategy is proposed based on historical information to maintain the validity of previous plan. Finally, empirical results are presented for the μRTS game, comparing AHTNR to the state-of-the-art search algorithms for RTS games.

Subject Areas

HTN planning; real-time strategy game; plan repair

Readers' Comments and Ratings (0)

Leave a public comment
Send a private comment to the author(s)
Rate this article
Views 0
Downloads 0
Comments 0
Metrics 0
Leave a public comment

×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.