Automatic tunable deployment for real-time strategy games
Article publication date: 18 April 2017
Extensive efforts have been conducted on the real-time strategy (RTS) games. The purpose of this paper is the specific artificial intelligence (AI) challenges posed by RTS games; non-player character (NPC) is started out by collecting game-map resources to build up defenses and attack forces, to upgrade combat deployment.
The authors used weak AI fuzzy theory as the foundation for tunable development. With the fuzzy theory, the AI was more humanistic in its judgment process.
Well-developed AIs have been used brilliantly in various aspects in RTS games, especially in those developed by large production teams. For small production teams, how to develop an AI system in less time and at a lower cost is extremely important.
This study aimed to develop a system using player unit threat levels for NPC deployment and arrangement so that the further strategy would be adopted for NPCs in response to player actions.
The RTS games would become more challenging for players to play.
Yang, C.-T., Yeh, H.-T., Chen, B.-C. and Jian, G.-X. (2017), "Automatic tunable deployment for real-time strategy games", Engineering Computations, Vol. 34 No. 2, pp. 239-250. https://doi.org/10.1108/EC-08-2015-0251
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