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Creating a Personality System for RTS Bots

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Abstract

Bots in Real Time Strategy games often play according to predefined scripts, which usually makes their behaviour repetitive and predictable. In this chapter, we discuss a notion of personality for an RTS bot and how it can be used to control a bot’s behaviour. We introduce a personality system that allows us to easily create different personalities and we discuss how different components of the system can be identified and defined. The process of personality creation is based on several traits, which describe a general bot’s characteristics. It allows us to create a wide variety of consistent personalities with the desired level of randomness, and, at the same time, to precisely control a bot’s behaviour by enforcing or preventing certain strategies and techniques.

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Notes

  1. 1.

    For an in-depth discussion of Turing Test variants and the meaning of intelligence in computer games see [12, 13].

  2. 2.

    exp a short for expansion, which is what resource bases in StarCraft are sometimes called.

  3. 3.

    It is interesting that such imitation may have an impact not only on the credibility, but also effectiveness of the bot. The winner of one of the tournaments (Tournament 3: Tech-Limited Game) during StarCraft AI Competition at AIIDE 2010 was Mimic Bot, which tried to imitate the movements of the enemy. Results of the tournament can be found on http://eis.ucsc.edu/Tournament3Results.

References

  1. http://us.blizzard.com/en-us/games/sc/. Accessed Jan 2011

  2. http://www.microsoft.com/games/empires/. Accessed Jan 2011

  3. http://starcraft.wikia.com/wiki/Actions_per_minute

  4. http://arstechnica.com/gaming/news/2010/07/excellence-of-execution-video-of-starcraft-mastery.ars

  5. http://wiki.teamliquid.net/starcraft/Mutalisk_vs_Scourge_Control#Method_2_:_The_Chinese_Triangle_Method. Accessed Jan 2011

  6. http://wiki.teamliquid.net/starcraft/Mutalisk_Harassment#Grouping

  7. http://wiki.teamliquid.net/starcraft/Magic_Boxes

  8. Beume, N., Hein, T., Naujoks, B., Piatkowski, N., Preuss, M., Wessing, S.: Intelligent anti-grouping in real-time strategy games. In: IEEE Symposium on Computational Intelligence and Games, pp. 63–70 (2008)

    Google Scholar 

  9. Buro, M.: Call for AI research in RTS games. In: Proceedings of the AAAI Workshop on AI in Games, pp. 139–141 (2004)

    Google Scholar 

  10. Buro, M., Furtak, T.M.: RTS games and real-time AI research. In: Proceedings of the Behavior Representation in Modeling and Simulation Conference, pp. 51–58 (2004)

    Google Scholar 

  11. Chung, M., Buro, M., Schaeffer, J.: Monte Carlo planning in RTS games, In: IEEE Symposium on Computational Intelligence and Games (2005)

    Google Scholar 

  12. Hingston, P.: A Turing test for computer game bots. IEEE Trans. Comput. Intell. AI Games 1(3), 169–186 (2009)

    Google Scholar 

  13. Livingstone, D.: Turing’s test and believable AI in games. Comput. Entertainment 4(1), Article 6 (2006)

    Google Scholar 

  14. Olesen, J.K., Yannakakis, G.N., Hallam, J.: Real-time challenge balance in an RTS game using rtNEAT. In: IEEE Symposium On Computational Intelligence and Games, pp. 87–94 (2008)

    Google Scholar 

  15. Sailer, F., Buro, M., Lanctot, M.: Adversarial planning through strategy simulation. In: IEEE Symposium on Computational Intelligence and Games, pp. 80–87 (2007)

    Google Scholar 

  16. Sweetser, P., Johnson, D., Sweetser, J., Wiles, J.: Creating engaging artificial characters for games. In: Proceedings of the Second International Conference on Entertainment Computing, pp. 1–8 (2003)

    Google Scholar 

  17. Tozour, P.: Influence mapping. In: Deloura, M. (ed.) Game Programming Gems 2, pp. 287–297. Charles River Media, Hingham (2001)

    Google Scholar 

  18. Tozour, P.: Strategic assessment techniques. In: Deloura, M. (ed.) Game Programming Gems 2, pp. 298–306. Charles River Media, Hingham (2001)

    Google Scholar 

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Acknowledgments

Special thanks are due to Marta Buchlovská for her help with the design of the last experiment. Also, thanks to all the participants of that tournament.

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Correspondence to Jacek Mańdziuk .

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Mańdziuk, J., Szałaj, P. (2013). Creating a Personality System for RTS Bots. In: Hingston, P. (eds) Believable Bots. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32323-2_10

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  • DOI: https://doi.org/10.1007/978-3-642-32323-2_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32322-5

  • Online ISBN: 978-3-642-32323-2

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