A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft

Santiago Ontañon (1) , Gabriel Synnaeve (2) , Alberto Uriarte (1) , Florian Richoux (3) , David Churchill (4) , Mike Preuss (5)

1 Computer Science Department [Drexel]
2 LSCP - Laboratoire de sciences cognitives et psycholinguistique
3 TASC - Theory, Algorithms and Systems for Constraints
4 Department of Computing Science [Edmonton]
5 Computer Science Department [Dortmund]

This paper presents an overview of the existing work on AI for real-time strategy (RTS) games. Specifically, we focus on the work around the game StarCraft, which has emerged in the past few years as the unified test-bed for this research. We describe the specific AI challenges posed by RTS games, and overview the solutions that have been explored to address them. Additionally, we also present a summary of the results of the recent StarCraft AI competitions, describing the architectures used by the participants. Finally, we conclude with a discussion emphasizing which problems in the context of RTS game AI have been solved, and which remain open.

Mots clés: Game AI; Real-Time Strategy; StarCraft

Domaines: Intelligence artificielle [cs.AI]

Santiago Ontañon, Gabriel Synnaeve, Alberto Uriarte, Florian Richoux, David Churchill, et al.. A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft. IEEE Transactions on Computational Intelligence and AI in games, 2013, 5 (4), pp.1-19. ⟨hal-00871001⟩