Analysis of selected methods of creating artificial intelligence on the example of a popular card game

Łukasz Gałka

lukasz.galka2@pollub.edu.pl
Lublin University of Technology (Poland)

Mariusz Dzieńkowski


Lublin University of Technology

Abstract

The aim of the article was to analyze selected methods of creating artificial intelligence in a popular card game. Two experiments were conducted: with a human and with a computer. The following algorithms were analyzed: random, min-max, based on a neural network, statistical and statistical with the use of "cheating" technique. The examined parameters were as follows: efficiency, execution time, number of implementation code lines, implementation time and training duration. The indicator with the greatest impact on the selection of the most optimal method was efficiency. The research has shown no difference in efficiency for the neural network-based algorithm and the statistical algorithm. In other cases, the differences in this feature were significant. The use of the "cheating" technique has increased the efficiency.


Keywords:

artificial intelligence; machine learning; algorithm efficiency evaluation; computer games

D.S. Cohen, T.J. Park, S.A Bustamante, Producing Games: From Business and Budgets to Creativity and Design, Routledge, 2010.
  Google Scholar

T. Walsh, To zyje! Sztuczna inteligencja, Wydawnictwo Naukowe PWN, 2018.
  Google Scholar

K. Wołk, Zabawa ze sztuczna inteligencja, Psychoskok, 2018.
  Google Scholar

S. Nowaczyk, Frontiers in Artificial Intelligence and Applications, Thirteenth Scandinavian Conference on Artificial Intelligence, Tom 278, Holandia, 2015.
  Google Scholar

T. Burczynski, W. Cholewa, W. Moczulski, Methods of artificial intelligence, Silesian University of Technology, 2009.
  Google Scholar

S. Castellano, Artificial Intelligence, Genuine Learning, Talent Development, Tom 73, Wydanie 10, 2019.
  Google Scholar

J. Łeski, Systemy neuronowo-rozmyte, Wydawnictwo WNT, 2008.
  Google Scholar

L. Rutkowski, Metody i techniki sztucznej inteligencji, Wydawnictwo Naukowe PWN, 2009.
  Google Scholar

Z. Shi, Advanced Artificial Intelligence, World Scientific, Singapur, 2011.
DOI: https://doi.org/10.1142/7547   Google Scholar

B. Zohuri, M. Moghaddam, Neural Network Driven Artificial Intelligence: Decision Making Based on Fuzzy Logic. Nova Science Publisher, Nowy Jork, 2017.
  Google Scholar

N. Joshi, Hands-On Artificial Intelligence with Java for Beginners: Build Intelligent Apps Using Machine Learning and Deep Learning with Deeplearning4j, Packt Publishing, 2018.
  Google Scholar

Przeglad branzy gier wideo, https://www.wepc.com/news/video-game-statistics, [13.07.2020].
  Google Scholar

G.N. Yannakakis, J. Togelius, Artificial intelligence and games, Cham: Springer, 2018.
DOI: https://doi.org/10.1007/978-3-319-63519-4   Google Scholar

G.N. Yannakakis, J. Togelius, A Panorama of Artificial and Computational Intelligence in Games, IEEE Transactions on Computational Intelligence and AI in Games, 2015.
DOI: https://doi.org/10.1109/TCIAIG.2014.2339221   Google Scholar

D. Brackeen, Java: tworzenie gier, Wydawnictwo Helion, Gliwice, 2004.
  Google Scholar

J.S. Harbour, Beginning Java SE 6 Game Programming, MA: Course PTR, Boston, 2012.
  Google Scholar

B. Kaluza, Machine Learning in Java, Packt Publishing, 2016.
  Google Scholar

W. McAllister, J. Fritz, Programming Fundamentals Using Java: A Game Application Approach, Dulles, Virginia: Mercury Learning & Information, 2015.
  Google Scholar

S. Pieta, M. Scibisz, M. Wisniewski, Podstawy tworzenia interfejsu graficznego aplikacji desktopowych w jezyku Java, Oficyna Wydawnicza Politechniki Warszawskiej, 2019.
  Google Scholar

S.K. Aditya, P. Mohanta, V. K. Karn, Android SQLite Essentials, Packt Publishing, 2014.
  Google Scholar

R.A. Johnson, Java Database Connectivity Using Sqlite: A Tutorial, Java Database Connectivity Using Sqlite: A Tutorial, Proceedings of the Academy of Information & Management Sciences, 2014.
  Google Scholar

B. Rigal, S. Kupisz, Gry karciane, Helion, 2007.
  Google Scholar

B. Whiter, J. Kluzinski, Gry karciane, K.E. Liber 2004.
  Google Scholar

T.B. Alakus, R. Das, I. Turkoglu, An Overview of Quality Metrics Used in Estimating Software Faults, International Artificial Intelligence and Data Processing Symposium, 2019.
DOI: https://doi.org/10.1109/IDAP.2019.8875925   Google Scholar

L. Buglione, A. Abran, Measurement Process: Improving the ISO 15939 Standard, Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement, 2014.
DOI: https://doi.org/10.1109/IWSM.Mensura.2014.39   Google Scholar

Dokumentacja oprogramowania CLOC, https://github.com/AlDanial/cloc, [13.07.2020].
  Google Scholar

Download


Published
2020-09-30

Cited by

Gałka, Łukasz, & Dzieńkowski, M. (2020). Analysis of selected methods of creating artificial intelligence on the example of a popular card game. Journal of Computer Sciences Institute, 16, 233–240. https://doi.org/10.35784/jcsi.2194

Authors

Łukasz Gałka 
lukasz.galka2@pollub.edu.pl
Lublin University of Technology Poland

Authors

Mariusz Dzieńkowski 

Lublin University of Technology

Statistics

Abstract views: 366
PDF downloads: 282