Hierarchical Task Network Plan Reuse for Video Games

Dennis J. N. J. Soemers*, Mark H. M. Winands

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review


Hierarchical Task Network Planning is an Automated Planning technique. It is, among other domains, used in Artificial Intelligence for video games. Generated plans cannot always be fully executed, for example due to nondeterminism or imperfect information. In such cases, it is often desirable to re-plan. This is typically done completely from scratch, or done using techniques that require conditions and effects of tasks to be defined in a specific format (typically based on First-Order Logic). In this paper, an approach for Plan Reuse is proposed that manipulates the order in which the search tree is traversed by using a similarity function. It is tested in the SimpleFPS domain, which simulates a First-Person Shooter game, and shown to be capable of finding (optimal) plans with a decreased amount of search effort on average when re-planning for variations of previously solved problems.
Original languageEnglish
Title of host publication2016 IEEE Conference on Computational Intelligence and Games (CIG)
Number of pages8
Publication statusPublished - Sept 2016
Event2016 IEEE Conference on Computational Intelligence and Games (CIG) - Petros M. Nomikos Conference Centre, Santorini, Greece
Duration: 20 Sept 201623 Sept 2016

Publication series

SeriesIEEE Conference on Computational Intelligence and Games


Conference2016 IEEE Conference on Computational Intelligence and Games (CIG)

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