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A Competitive Combat Strategy and Tactics in RTS Games AI and StarCraft

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Advances in Multimedia Information Processing – PCM 2017 (PCM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10736))

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Abstract

This paper presents a competitive combat strategy and tactics in RTS Games AI. To put it simply, if a player is building up base, he is losing out on creating an army and If he is building up his army, he is losing out on having a strong base. The key to winning, in StarCraft or any other RTS game is to balance strategy, tactics, macro and micro. To improve the game, one has to be able to keep track of everything that’s going on over the entire map. And one must be able to give orders quickly and efficiently so in this paper we propose a competitive battle strategy with the help of a plot and decision tree. We simulate the strategy in MicroRTS developed in java EE by conducting a game-play between human player and MicroRTS AI (Game AI), though our proposed strategy out-performs the Game AI rarely as we did not account game playing-speed that makes a huge difference in victory but at least we succeeded in introducing a strategy that could well compete the Game AI and may defeat it but rarely.

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Acknowledgement

Thanks for the support provided by CSC and Department of Computer Science, HIT Harbin, China.

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People’s Republic of China

    Adil Khan, Worku Jifara, Feng Jiang & Liu Shaohui

  2. Chinese People’s Liberation Army Aviation School, Beijing, People’s Republic of China

    Kai Yang

  3. Institute of Computer Applications, China Academy of Engineering Physics, Mianyang, People’s Republic of China

    Yunsheng Fu & Fang Lou

Authors
  1. Adil Khan
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  2. Kai Yang
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  3. Yunsheng Fu
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  4. Fang Lou
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  5. Worku Jifara
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  6. Feng Jiang
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  7. Liu Shaohui
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Corresponding author

Correspondence to Adil Khan .

Editor information

Editors and Affiliations

  1. University of Electronic Science and Technology of China, Chengdu, China

    Bing Zeng

  2. University of Chinese Academy of Sciences, Beijing, China

    Qingming Huang

  3. University of Ottawa, Ottawa, Ontario, Canada

    Abdulmotaleb El Saddik

  4. University of Electronic Science and Technology of China, Chengdu, China

    Hongliang Li

  5. Chinese Academy of Sciences, Beijing, China

    Shuqiang Jiang

  6. Harbin Institute of Technology, Harbin, China

    Xiaopeng Fan

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Khan, A. et al. (2018). A Competitive Combat Strategy and Tactics in RTS Games AI and StarCraft. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10736. Springer, Cham. https://doi.org/10.1007/978-3-319-77383-4_1

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  • DOI: https://doi.org/10.1007/978-3-319-77383-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77382-7

  • Online ISBN: 978-3-319-77383-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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