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Type-2 Fuzzy Logic and Systems pp 105–127Cite as

Type-2 Fuzzy Logic Control in Computer Games

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 362))

Abstract

In this chapter, we will present the novel applications of the Interval Type-2 (IT2) Fuzzy Logic Controllers (FLCs) into the research area of computer games. In this context, we will handle two popular computer games called Flappy Bird and Lunar Lander. From a control engineering point of view, the game Flappy Bird can be seen as a classical obstacle avoidance while Lunar Lander as a position control problem. Both games inherent high level of uncertainties and randomness which are the main challenges of the game for the player. Thus, these two games can be seen as challenging testbeds for benchmarking IT2-FLCs as they provide dynamic and competitive elements that are similar to real-world control engineering problems. As the game player can be considered as the main controller in a feedback loop, we will construct an intelligent control systems composed of three main subsystems: reference generator, the main controller, and game dynamics. In this chapter, we will design and then employ an IT2-FLC as the main controller in a feedback loop such that to have a satisfactory game performance while be able to handle the various uncertainties of the games. In this context, we will briefly present the general structure and the design methods of two IT2-FLCs which are the Single Input and the Double Input IT2-FLCs. We will show that the IT2-FLC structure is capable to handle the uncertainties caused by the nature of the games by presenting both simulations and real-time game results in comparison with its Type-1 and conventional counterparts. We believe that the presented design methodology and results will provide a bridge for a wider deployment of Type-2 fuzzy logic in the area of the computer games.

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References

  1. S.M. Lucas, G. Kendall, Evolutionary computation and games. IEEE Comput. Intell. Mag. 1(1), 10–18 (2006)

    Article  Google Scholar 

  2. N. Cole, S.J. Louis, C. Miles, Using a genetic algorithm to tune first-person shooter bots, in Proceedings of IEEE Congress on Evolutionary Computing (2004), pp. 139–145

    Google Scholar 

  3. J. MacGlashan, M.L. Littman, Between imitation and intention learning, in Proceedings of International Conference on Artificial Intelligence (2015), pp. 3692–3698

    Google Scholar 

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

    Article  Google Scholar 

  5. S.M. Lucas, Evolving a neural network location evaluator to play ms. pac-man, in Proceedings of IEEE Symposium on Computational Intelligence and Games (2005), pp. 203–210

    Google Scholar 

  6. B. Sheppard, World-championship-caliber Scrabble. Artif. Intell. 134(1), 241–275 (2002)

    Article  MATH  Google Scholar 

  7. D. Perez, G. Recio, Y. Saez, P. Isasi, Evolving a fuzzy controller for a car racing competition, in Proceedings of IEEE Symposium on Computational Intelligence and Games, September 2009, pp. 263–270

    Google Scholar 

  8. W. Goufang, F. Zhou, L. Ping, L. Bo, Shaping in reinforcement learning via knowledge transferred from human demonstrations, in Proceedings of 34th Chinese Control Conference, Hangzhou, China, July 2015, pp. 3033–3038

    Google Scholar 

  9. S. Karakovskiy, J. Togelius, The mario ai benchmark and competitions. IEEE Trans Comput. Intell. AI Games 4(1), 55–67 (2012)

    Article  Google Scholar 

  10. S. Ontanón, G. Synnaeve, A. Uriarte, F. Richoux, D. Churchill, M. Preuss, A survey of real-time strategy game ai research and competition in starcraft. IEEE Trans. Comput. Intell. AI Games 5(4), 293–311 (2013)

    Google Scholar 

  11. B. Takacs, J. Holaza, J. Stevek, M. Kvasnica, Export of explicit model predictive control to python, in Proceedings of 20th International Conference on Process Control, Štrbské Pleso, Slovakia, June 2015, pp. 78–83

    Google Scholar 

  12. A. Sahin, E. Atici, T. Kumbasar, Type-2 fuzzified flappy bird control system, in Proceedings of IEEE International Conference on Fuzzy Systems (2016), pp. 1578–1583

    Google Scholar 

  13. M. Ebner, J. Levine, S.M. Lucas, T. Schaul, T. Thompson, J. Togelius, Towards a video game description language (2013). https://doi.org/10.4230/dfu.vol6.12191.85

  14. A. Sahin, T. Kumbasar, Landing on the moon with type-2 fuzzy logic, in Proceedings of IEEE International Conference on Fuzzy Systems (2017),​ pp. 1–6

    Google Scholar 

  15. J.M. Mendel, R.B. John, Type-2 fuzzy sets made simple. IEEE Trans. Fuzzy Syst. 10(2), 117–127 (2002)

    Article  Google Scholar 

  16. J.M. Mendel, H. Hagras, W.W Tan, W.W. Melek, H. Ying, Introduction to Type-2 Fuzzy Logic Control (John Wiley and IEEE Press, Hoboken, NJ, 2014)

    Google Scholar 

  17. H. Hagras, A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans. Fuzzy Syst. 12(4), 524–539 (2004)

    Article  Google Scholar 

  18. T. Kumbasar, H. Hagras, Big Bang–Big Crunch optimization based interval type-2 fuzzy pid cascade controller design strategy. Inform. Sci. 282, 277–295 (2014)

    Article  Google Scholar 

  19. A. Kumar, V. Kumar, Evolving an interval type-2 fuzzy PID controller for redundant robotic manipulator. Expert Syst. Appl. 73, 161–177 (2017)

    Article  Google Scholar 

  20. T. Kumbasar, H. Hagras, A self-tuning zSlices based general type-2 fuzzy PI controller. IEEE Trans. Fuzzy Syst. 23(4), 991–1013 (2015)

    Article  Google Scholar 

  21. M. Mehndiratta, E. Kayacan, T. Kumbasar, Design and experimental validation of single input type-2 fuzzy PID controllers as applied to 3 DOF helicopter testbed, in Proceedings of IEEE International Conference on Fuzzy Systems (2016), pp. 1584–1591

    Google Scholar 

  22. C. Lynch, H. Hagras, V. Callaghan, Embedded type-2 FLC for real-time speed control of marine and traction diesel engines, in Proceedings of IEEE International Conference on Fuzzy Systems (2005), pp. 347–352

    Google Scholar 

  23. E. Yesil, Interval type-2 fuzzy PID load frequency controller using Big Bang–Big Crunch optimization. Appl. Soft Comput. 15, 100–112 (2014)

    Article  Google Scholar 

  24. Q. Liang, J.M. Mendel, Interval type-2 fuzzy logic systems: theory and design. IEEE Trans. Fuzzy Syst. 8(5), 535–550 (2000)

    Article  Google Scholar 

  25. H. Wu, J.M. Mendel, Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 10(5), 622–639 (2002)

    Article  Google Scholar 

  26. T. Kumbasar, H. Hagras, Interval type-2 fuzzy PID controllers, in Springer Handbook of Computational Intelligence (Springer, Berlin, Heidelberg, 2015), pp. 285–294

    Google Scholar 

  27. T. Kumbasar, A simple design method for interval type-2 fuzzy PID controllers. Soft. Comput. 18(7), 1293–1304 (2014)

    Article  Google Scholar 

  28. T. Kumbasar, Robust stability analysis and systematic design of single input interval type-2 fuzzy logic controllers. IEEE Trans. Fuzzy Syst. 24(3), 675–694 (2015). https://doi.org/10.1109/TFUZZ.2015.2471805

  29. A. Taskin, T. Kumbasar, An open source Matlab/Simulink toolbox for interval type-2 fuzzy logic systems, in Proceedings of IEEE Symposium Series on Computational Intelligence (2015), pp. 1561–1568

    Google Scholar 

  30. A. Sakalli, T. Kumbasar, M.F. Dodurka, E. Yesil, The simplest Interval type-2 fuzzy PID controller: structural analysis, in Proceedings of IEEE International Conference on Fuzzy Systems (2014), pp. 626–633

    Google Scholar 

  31. A. Sakalli, T. Kumbasar, On the fundamental differences between the NT and the KM center of sets calculation methods on the IT2-FLC performance, in Proceedings of IEEE International Conference on Fuzzy Systems (2015), pp. 1–8

    Google Scholar 

  32. A. Sakalli, A. Bekea, T. Kumbasar, Gradient descent and extended kalman filter based self-tuning interval type-2 fuzzy PID controllers, in Proceedings of IEEE International Conference on Fuzzy Systems (2016), pp. 1592–1598

    Google Scholar 

  33. A. Isaksen, D. Gopstein, A. Nealen, Exploring game space using survival analysis, in Foundations of Digital Games (2015)

    Google Scholar 

  34. M. Zhang, Flappy bird for MATLAB, http://www.mathworks.com/matlabcentral/fileexchange/45795-flappy-bird-for-matlab. 25 Oct 2015

  35. W.-C. So, C.K. Tse, Y.-S. Lee, Development of a fuzzy logic controller for dc–dc converters: design, computer simulation, and experimental evaluation. IEEE Trans. Power Electron. 11(1), 24–32 (1996)

    Article  Google Scholar 

  36. B. Edwards, Forty years of Lunar Lander, Technologizer (2009), http://www.technologizer.com/2009/07/19/lunar-lander/. Accessed 02 Jan 2017

  37. S. Samothrakis, S.A. Roberts, D. Perez, S.M. Lucas, Rolling horizon methods for games with continuous states and actions, in Proceedings of IEEE Conference on Computational Intelligence in Games (2014), pp. 1–8

    Google Scholar 

  38. S.A. Roberts, S.M. Lucas, Measuring interestingness of continuous game problems, in Proceedings of IEEE Conference on Computational Intelligence in Games (2013) pp. 1–8

    Google Scholar 

  39. H. Corte, Moon Lander matlab game (2012), https://uk.mathworks.com/matlabcentral/fileexchange/38927. Accessed 02 Jan 2017

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Author information

Authors and Affiliations

  1. Centre for Process Analytics and Control Technology, University of Strathclyde, Glasgow, G1 1XL, UK

    Atakan Sahin

  2. Control and Automation Engineering Department, Istanbul Technical University, 34469, Istanbul, Turkey

    Tufan Kumbasar

Authors
  1. Atakan Sahin
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  2. Tufan Kumbasar
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Correspondence to Atakan Sahin .

Editor information

Editors and Affiliations

  1. LUCID Research Group, School of Computer Science, The University of Nottingham, Jubilee Campus, Nottingham, Nottinghamshire, United Kingdom

    Robert John

  2. School of Computer Science and Electronic Engineering, The Computational Intelligence Centre, University of Essex, Colchester, United Kingdom

    Hani Hagras

  3. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

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Sahin, A., Kumbasar, T. (2018). Type-2 Fuzzy Logic Control in Computer Games. In: John, R., Hagras, H., Castillo, O. (eds) Type-2 Fuzzy Logic and Systems. Studies in Fuzziness and Soft Computing, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-319-72892-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-72892-6_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72891-9

  • Online ISBN: 978-3-319-72892-6

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