Walling in Strategy Games via Constraint Optimization

This paper presents a constraint optimization approach to walling in real-time strategy (RTS) games. Walling is a specific type of spatial reasoning, typically employed by human expert players and not currently fully exploited in RTS game AI, consisting on finding configurations of buildings to completely or partially block paths. Our approach is based on local search, and is specifically designed for the real-time nature of RTS games. We present experiments in the context of the RTS game StarCraft showing promising results.

[1]  Michael Buro,et al.  Real-Time Strategy Games: A New AI Research Challenge , 2003, IJCAI.

[2]  Carlos Cotta,et al.  A self-adaptive evolutionary approach to the evolution of aesthetic maps for a RTS game , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[3]  Luke Perkins,et al.  Terrain Analysis in Real-Time Strategy Games: An Integrated Approach to Choke Point Detection and Region Decomposition , 2010, AIIDE.

[4]  Michael Buro,et al.  Real-Time Strategy Game Competitions , 2012, AI Mag..

[5]  Santiago Ontañón,et al.  A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft , 2013, IEEE Transactions on Computational Intelligence and AI in Games.

[6]  Johan Hagelbäck,et al.  Potential-field based navigation in StarCraft , 2012, 2012 IEEE Conference on Computational Intelligence and Games (CIG).

[7]  Philippe Codognet,et al.  Large-scale parallelism for constraint-based local search: the costas array case study , 2014, Constraints.

[8]  Jack Bresenham,et al.  Algorithm for computer control of a digital plotter , 1965, IBM Syst. J..

[9]  Anthony G. Cohn,et al.  A Spatial Logic based on Regions and Connection , 1992, KR.

[10]  Michal Certický,et al.  Implementing a Wall-In Building Placement in StarCraft with Declarative Programming , 2013, ArXiv.

[11]  Kenneth D. Forbus.  Handbook of Knowledge Representation Edited Qualitative Modeling , 2022 .

[12]  James F. Allen.  Towards a General Theory of Action and Time , 1984, Artif. Intell..

[13]  Philippe Codognet,et al.  Yet Another Local Search Method for Constraint Solving , 2001, SAGA.

[14]  Julian Togelius,et al.  Towards multiobjective procedural map generation , 2010, PCGames@FDG.

[15]  Chek Tien Tan,et al.  Automated terrain analysis in real-time strategy games , 2014, FDG.

[16]  Santiago Ontañón,et al.  Kiting in RTS Games Using Influence Maps , 2012, Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment.

[17]  Frank van Harmelen,et al.  Handbook of Knowledge Representation , 2008, Handbook of Knowledge Representation.

[18]  Bernhard Nebel,et al.  Qualitative Spatio-Temporal Reasoning with RCC-8 and Allen's Interval Calculus: Computational Complexity , 2002, ECAI.

[19]  Günter Rudolph,et al.  Multi-objective assessment of pre-optimized build orders exemplified for StarCraft 2 , 2013, 2013 IEEE Conference on Computational Inteligence in Games (CIG).

[20]  Michael Buro,et al.  Build Order Optimization in StarCraft , 2011, AIIDE.