Automatic tunable deployment for real-time strategy games

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implication

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.

Originality/value

The RTS games would become more challenging for players to play.

Citation

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