Penerapan Algoritma Monte Carlo Tree Search pada Permainan Halma
61
DAFTAR PUSTAKA
Arneson, B., Hayward, R. B., & Henderson, P. 2010. Monte Carlo Tree Search in Hex.
IEEE Transactions on Computational Intelligence and AI in Games 2(4): 251258.
Auer, P., Cesa-Bianchi, N., & Fischer, P. 2002. Finite-Time Analysis Of The
Multiarmed Bandit Problem. Machine Learning 47(2-3): 235-256.
Bell, G. I. 2009. The Shortest Game of Chinese Checkers and Related Problems.
Integers : Electronic Journal of Combinatorial Number Theory 9(1):17-39.
Browne, C. B., Powley, E., Whitehouse, D., Lucas, S. M., Cowling, P. I., Rohlfshagen,
P., & Colton, S. 2012. A Survey Of Monte Carlo Tree Search Methods. IEEE
Transactions on Computational Intelligence and AI in Games 4(1): 1-43.
Chaslot, G. 2010. Monte-Carlo Tree Search. Tesis. Universiteit of Maastricht.
Chaslot, G., Bakkes, S., Szita, I. & Spronck, P. 2008. Monte-Carlo Tree Search: A New
Framework for Game AI. Proceedings of the Fourth Artificial Intelligence and
Interactive Digital Entertainment Conference, pp 216-217.
Chaslot, G., Winands, M., Uiterwijk, J., van den Herik, H., & Bouzy, B. 2007.
Progressive Strategies for Monte-Carlo Tree Search. In Proceedings of the 10th
Joint Conference on Information Sciences (JCIS 2007), pp. 655-661.
Coppin, B. 2004. Artificial Intelligence Illuminated. Jones & Bartlett Learning:
Massachusetts.
62
Elnaggar, A. A., Abdel, M., Gadallah, M., & El-Deeb, H. 2014. A Comparative Study
Of Game Tree Searching Methods. International Journal of Advanced
Computer Science and Applications 5(5): 68-77.
Gelly, S., Kocsis, L., Schoenauer, M., Sebag, M., Silver, D., Szepesvári, C., & Teytaud,
O. 2012. The Grand Challenge of Computer Go: Monte Carlo Tree Search and
Extensions. Communications of the ACM 55(3): 106-113.
Indah, M. N. 2011. Aplikasi Permainan Halma Secara Multiplayer Dengan Metode
Depth First Search. PETIR : Jurnal Pengkajian dan Penerapan Teknik
Informatika 4(1):15-23.
Kocsis, L., & Szepesvári, C. 2006. Bandit Based Monte-Carlo Planning. European
Conference on Machine Learning, pp. 282-293
Lieyanda, V. 2011. Penerapan Algoritma Greedy untuk Permainan Halma. Makalah
Strategi Algoritma. Institut Teknologi Bandung.
Magnuson, M. 2015. Monte Carlo Tree Search and Its Applications. Scholarly
Horizons: University of Minnesota, Morris Undergraduate Journal 2(2): 1-6.
Millington, I. & Funge, J. 2009. Artificial intelligence for games. 2nd Edition. Morgan
Kaufmann: Amsterdam.
Nijssen, J. P. A. M. 2007. Playing Othello Using Monte Carlo. Strategies 22:1-9.
Russell, S. & Norvig, P. 1995. A Modern Approach. Artificial Intelligence. PrenticeHall: New Jersey.
Salen, K. & Zimmerman, E. 2004. Rules of Play: Game Design Fundamentals. MIT
press: London.
63
Schaeffer, J. 2000. The Games Computers (and People) Play. Advances in Computers
52:189-166.
Schwab, B. 2009. AI Game Engine Programming. Nelson Education: Canada.
Turocy, T. L. & von Stengel, B. 2001. Game Theory. CDAM Research Report.
Van der Kleij, A. A. J. 2010. Monte Carlo Tree Search And Opponent Modeling
Through Player Clustering In No-Limit Texas Hold’em Poker. Tesis. University
of Groningen, The Netherlands.
Walker, D. 2011. Halma, Grasshopper & Chinese Checkers. Traditional Board Game
Series.
Winands, M. H., Bjornsson, Y., & Saito, J. T. 2010. Monte Carlo Tree Search in Lines
of Action. IEEE Transactions on Computational Intelligence and AI in Games
2(4): 239-250.
DAFTAR PUSTAKA
Arneson, B., Hayward, R. B., & Henderson, P. 2010. Monte Carlo Tree Search in Hex.
IEEE Transactions on Computational Intelligence and AI in Games 2(4): 251258.
Auer, P., Cesa-Bianchi, N., & Fischer, P. 2002. Finite-Time Analysis Of The
Multiarmed Bandit Problem. Machine Learning 47(2-3): 235-256.
Bell, G. I. 2009. The Shortest Game of Chinese Checkers and Related Problems.
Integers : Electronic Journal of Combinatorial Number Theory 9(1):17-39.
Browne, C. B., Powley, E., Whitehouse, D., Lucas, S. M., Cowling, P. I., Rohlfshagen,
P., & Colton, S. 2012. A Survey Of Monte Carlo Tree Search Methods. IEEE
Transactions on Computational Intelligence and AI in Games 4(1): 1-43.
Chaslot, G. 2010. Monte-Carlo Tree Search. Tesis. Universiteit of Maastricht.
Chaslot, G., Bakkes, S., Szita, I. & Spronck, P. 2008. Monte-Carlo Tree Search: A New
Framework for Game AI. Proceedings of the Fourth Artificial Intelligence and
Interactive Digital Entertainment Conference, pp 216-217.
Chaslot, G., Winands, M., Uiterwijk, J., van den Herik, H., & Bouzy, B. 2007.
Progressive Strategies for Monte-Carlo Tree Search. In Proceedings of the 10th
Joint Conference on Information Sciences (JCIS 2007), pp. 655-661.
Coppin, B. 2004. Artificial Intelligence Illuminated. Jones & Bartlett Learning:
Massachusetts.
62
Elnaggar, A. A., Abdel, M., Gadallah, M., & El-Deeb, H. 2014. A Comparative Study
Of Game Tree Searching Methods. International Journal of Advanced
Computer Science and Applications 5(5): 68-77.
Gelly, S., Kocsis, L., Schoenauer, M., Sebag, M., Silver, D., Szepesvári, C., & Teytaud,
O. 2012. The Grand Challenge of Computer Go: Monte Carlo Tree Search and
Extensions. Communications of the ACM 55(3): 106-113.
Indah, M. N. 2011. Aplikasi Permainan Halma Secara Multiplayer Dengan Metode
Depth First Search. PETIR : Jurnal Pengkajian dan Penerapan Teknik
Informatika 4(1):15-23.
Kocsis, L., & Szepesvári, C. 2006. Bandit Based Monte-Carlo Planning. European
Conference on Machine Learning, pp. 282-293
Lieyanda, V. 2011. Penerapan Algoritma Greedy untuk Permainan Halma. Makalah
Strategi Algoritma. Institut Teknologi Bandung.
Magnuson, M. 2015. Monte Carlo Tree Search and Its Applications. Scholarly
Horizons: University of Minnesota, Morris Undergraduate Journal 2(2): 1-6.
Millington, I. & Funge, J. 2009. Artificial intelligence for games. 2nd Edition. Morgan
Kaufmann: Amsterdam.
Nijssen, J. P. A. M. 2007. Playing Othello Using Monte Carlo. Strategies 22:1-9.
Russell, S. & Norvig, P. 1995. A Modern Approach. Artificial Intelligence. PrenticeHall: New Jersey.
Salen, K. & Zimmerman, E. 2004. Rules of Play: Game Design Fundamentals. MIT
press: London.
63
Schaeffer, J. 2000. The Games Computers (and People) Play. Advances in Computers
52:189-166.
Schwab, B. 2009. AI Game Engine Programming. Nelson Education: Canada.
Turocy, T. L. & von Stengel, B. 2001. Game Theory. CDAM Research Report.
Van der Kleij, A. A. J. 2010. Monte Carlo Tree Search And Opponent Modeling
Through Player Clustering In No-Limit Texas Hold’em Poker. Tesis. University
of Groningen, The Netherlands.
Walker, D. 2011. Halma, Grasshopper & Chinese Checkers. Traditional Board Game
Series.
Winands, M. H., Bjornsson, Y., & Saito, J. T. 2010. Monte Carlo Tree Search in Lines
of Action. IEEE Transactions on Computational Intelligence and AI in Games
2(4): 239-250.