Automatic state abstraction for pathfinding in real-time video games

Authors:
Nathan Sturtevant;Vadim Bulitko;Michael Buro
Affiliations:
Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada;Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada;Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada
Venue:
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Year:
2005

Citing 3
Cited 0

Speeding up learning in real-time search via automatic state abstraction

AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Learning in real-time search: a unifying framework

Journal of Artificial Intelligence Research
Hierarchical A *: searching abstraction hierarchies efficiently

AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

Real-time video games are a unique domain for pathfinding and search. Traditional approaches to search have usually assumed static worlds with a single agent. But, in real-time video games there are multiple cooperative and adversarial agents. While the search space in most games is relatively small, algorithms are expected to plan in mere milliseconds. Thus, techniques such as abstraction are needed to effectively reason and act in these worlds. We provide an overview of the research we have completed in this area, as well as areas of current and future work.