Othello Game Application Design Using Heuristic Techniques

Authors

  • Leo Benny Institut Teknologi Manajemen Internasional (ITMI)
  • Lusi Herlina Institut Teknologi Manajemen Internasional (ITMI)

Keywords:

Game, Othello, Heuristic

Abstract

Othello is a popular board game and is played by two players. Problems arise when there are no friends to play with or the player does not have a game device. To solve this problem, an Othello game application can be developed, so that players can play Othello against the computer. Research applies heuristic techniques in the game Othello. The heuristic technique calculates the number of player chips (points) that the computer can turn over on each tile or square. This number of points is then multiplied by the coefficient value of 1.5 if the square is on the side of the game, while the points obtained from the box in the corner of the board are multiplied by the coefficient value of 3. In the end, the computer will choose the box with the highest heuristic value. Thus, the heuristic technique will prioritize the placement of the pieces in the corner of the board, the side of the board and then the placement of the pieces in the middle of the board. The application applies artificial intelligence to the computer by using heuristic techniques, so that the computer will prioritize the placement of chips at the corners and edges of the board whenever possible.

References

Ashlesh, P., Deepak, K. K., & Preet, K. K. (2020). Role of the prefrontal cortex during Sudoku task: fNIRS study. Translational neuroscience, 11(1), 419-427.

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901.

Chang, N. Y., Chen, C. H., Lin, S. S., & Nair, S. (2018). The big win strategy on multi-value network: An improvement over Alphazero approach for 6x6 Othello. In Proceedings of the 2018 International Conference on Machine Learning and Machine Intelligence (pp. 78-81).

Ciolino, M., Kalin, J., & Noever, D. (2020). The Go Transformer: Natural Language Modeling for Game Play. In 2020 Third International Conference on Artificial Intelligence for Industries (AI4I) (pp. 23-26). IEEE.

Goecks, V. G., Waytowich, N., Asher, D. E., Jun Park, S., Mittrick, M., Richardson, J., & Kott, A. (2022). On games and simulators as a platform for development of artificial intelligence for command and control. The Journal of Defense Modeling and Simulation, 15485129221083278

Kastha, P. (2020). Comparison of Heuristic Methods In The Othello Game. International Research Journal of Modernization in Engineering Technology and Science (IRJMETS), 2(12), p.996-1000

Liskowski, P., Jaśkowski, W., & Krawiec, K. (2018). Learning to play Othello with deep neural networks. IEEE Transactions on Games, 10(4), 354-364

Moy, G., Shekh, S., Oxenham, M., & Ellis-Steinborner, S. (2020). Recent Advances in Artificial Intelligence and their Impact on Defence.

Noever, Samantha & Noever, D.. (2022). Word Play for Playing Othello (Reverses). 10.48550/arXiv.2207.08766.

Nugraha, Y.S., Darusalam, U., Iskandar, A. (2022). Implementasi Algoritma Genetika pada Perancangan Aplikasi Penjadwalan Instalasi Antivirus Berbasis Websitemenggunakan Metode Waterfall. Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) 6(1), 117-129

Primanita, Anggina, Mohd Nor Akmal Khalid, & Hiroyuki Iida. (2020). "Characterizing the Nature of Probability-Based Proof Number Search: A Case Study in the Othello and Connect Four Games" Information 11( 5): 264. https://doi.org/10.3390/info11050264

Ranjitha M., Nathan, K., and Joseph, L. (2020). Artificial Intelligence Algorithms and Techniques in the computation of PlayerAdaptive Games. Journal of Physics: Conference Series, 1427 (2020) 012006 IOP Publishing doi:10.1088/1742-6596/1427/1/012006

Schrittwieser, J., Antonoglou, I., Hubert, T., Simonyan, K., Sifre, L., Schmitt, S., & Silver, D. (2020). Mastering atari, go, chess and shogi by planning with a learned model. Nature, 588(7839), 604-609.

Sobieski, W. (2022). Waterfall Algorithm as a tool of investigation the geometrical features of granular porous media. Comp. Part. Mech. 9, 551–567. https://doi.org/10.1007/s40571-021-00430-0

Song, Z.; Iida, H.; Van Den Herik, H.J. (2019). Probability based Proof Number Search. In Proceedings of the 11th International Conference on Agents and Artificial Intelligence, Prague, Czech Republic, 19–21.

Thakoor, S., Nair, S., & Jhunjhunwala, M. (2018). Learning to play Othello without human knowledge. Stanford University CS238 Final Project Report, 204, 257

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Published

2022-10-09

How to Cite

Benny, L., & Herlina, L. . (2022). Othello Game Application Design Using Heuristic Techniques. Jurnal Mandiri IT, 11(2), 73–80. Retrieved from http://ejournal.isha.or.id/index.php/Mandiri/article/view/164