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Automatic tunable deployment for real-time strategy games

Automatic tunable deployment for real-time strategy games PurposeExtensive 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/approachThe 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.FindingsWell-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/implicationThis 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/valueThe RTS games would become more challenging for players to play. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Engineering Computations Emerald Publishing

Automatic tunable deployment for real-time strategy games

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0264-4401
DOI
10.1108/EC-08-2015-0251
Publisher site
See Article on Publisher Site

Abstract

PurposeExtensive 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/approachThe 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.FindingsWell-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/implicationThis 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/valueThe RTS games would become more challenging for players to play.

Journal

Engineering Computations – Emerald Publishing

Published: Apr 18, 2017

References

  • Combining AI methods for learning bots in a real-time strategy game
  • DCA dynamic challenging level adapter for realtime strategy games