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IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, VOL. 4, NO. 1, MARCH 2012 44<br />

Int. Euro. Conf. Parallel Distrib. Comput., LNCS 6853, Bordeaux,<br />

France, 2011, pp. 365–376.<br />

[99] S. He, Y. Wang, F. Xie, J. Meng, H. Chen, S. Luo, Z. Liu, and<br />

Q. Zhu, “Game Player Strategy Pattern Recognition and How<br />

UCT Algorithms Apply Pre-knowledge <strong>of</strong> Player’s Strategy<br />

to Improve Opponent AI,” in Proc. 2008 Int. Conf. Comput.<br />

Intell. Model. Control Automat., Vienna, Austria, Dec. 2008, pp.<br />

1177–1181.<br />

[100] S. He, F. Xie, Y. Wang, S. Luo, Y. Fu, J. Yang, Z. Liu, and<br />

Q. Zhu, “To Create Adaptive Game Opponent by Using UCT,”<br />

in Proc. 2008 Int. Conf. Comput. Intell. Model. Control Automat.,<br />

Vienna, Austria, Dec. 2008, pp. 67–70.<br />

[101] D. P. Helmbold and A. Parker-Wood, “All-Moves-As-First<br />

Heuristics in <strong>Monte</strong>-<strong>Carlo</strong> Go,” in Proc. Int. Conf. Artif. Intell.,<br />

Las Vegas, Nevada, 2009, pp. 605–610.<br />

[102] B. Helmstetter, C.-S. Lee, F. Teytaud, O. Teytaud, M.-H. Wang,<br />

and S.-J. Yen, “Random positions in Go,” in Proc. IEEE Conf.<br />

Comput. Intell. Games, Seoul, South Korea, 2011, pp. 250–257.<br />

[103] P. Hingston and M. Masek, “Experiments with <strong>Monte</strong> <strong>Carlo</strong><br />

Othello,” in Proc. IEEE Congr. Evol. Comput., Singapore, 2007,<br />

pp. 4059–4064.<br />

[104] J.-B. Hoock, C.-S. Lee, A. Rimmel, F. Teytaud, O. Teytaud, and<br />

M.-H. Wang, “Intelligent Agents for the Game <strong>of</strong> Go,” IEEE<br />

Comput. Intell. Mag., vol. 5, no. 4, pp. 28–42, 2010.<br />

[105] J.-B. Hoock and O. Teytaud, “Bandit-Based Genetic<br />

Programming,” in Proc. Euro. Conf. Gen. Prog., vol. 6021,<br />

Istanbul, Turkey, 2010, pp. 268–277.<br />

[106] J. Huang, Z. Liu, B. Lu, and F. Xiao, “Pruning in UCT<br />

Algorithm,” in Proc. Int. Conf. Tech. Applicat. Artif. Intell.,<br />

Hsinchu, Taiwan, 2010, pp. 177–181.<br />

[107] S.-C. Huang, “New Heuristics for <strong>Monte</strong> <strong>Carlo</strong> <strong>Tree</strong> <strong>Search</strong><br />

Applied to the Game <strong>of</strong> Go,” Ph.D. dissertation, Nat. Taiwan<br />

Normal Univ., Taipei, 2011.<br />

[108] S.-C. Huang, R. Coulom, and S.-S. Lin, “<strong>Monte</strong>-<strong>Carlo</strong> Simulation<br />

Balancing Applied to 9x9 Go,” Int. Comp. Games Assoc. J., vol. 33,<br />

no. 4, pp. 191–201, 2010.<br />

[109] ——, “<strong>Monte</strong>-<strong>Carlo</strong> Simulation Balancing in Practice,” in Proc.<br />

Comput. and Games, LNCS 6515, Kanazawa, Japan, 2010, pp.<br />

81–92.<br />

[110] ——, “Time Management for <strong>Monte</strong>-<strong>Carlo</strong> <strong>Tree</strong> <strong>Search</strong> Applied<br />

to the Game <strong>of</strong> Go,” in Proc. Int. Conf. Tech. Applicat. Artif.<br />

Intell., Hsinchu City, Taiwan, 2010, pp. 462–466.<br />

[111] N. Ikehata and T. Ito, “<strong>Monte</strong> <strong>Carlo</strong> <strong>Tree</strong> <strong>Search</strong> in Ms. Pac-Man,”<br />

in Proc. 15th Game Progr. Workshop, Kanagawa, Japan, 2010, pp.<br />

1–8.<br />

[112] ——, “<strong>Monte</strong>-<strong>Carlo</strong> <strong>Tree</strong> <strong>Search</strong> in Ms. Pac-Man,” in Proc. IEEE<br />

Conf. Comput. Intell. Games, Seoul, South Korea, 2011, pp. 39–46.<br />

[113] H. Kato and I. Takeuchi, “Parallel <strong>Monte</strong>-<strong>Carlo</strong> <strong>Tree</strong> <strong>Search</strong><br />

with Simulation Servers,” in Proc. Int. Conf. Tech. Applicat. Artif.<br />

Intell., Hsinchu City, Taiwan, 2010, pp. 491–498.<br />

[114] J. Kloetzer, “Experiments in <strong>Monte</strong>-<strong>Carlo</strong> Amazons,” J. Inform.<br />

Process. Soc. Japan, vol. 2010-GI-24, no. 6, pp. 1–4, 2010.<br />

[115] ——, “<strong>Monte</strong>-<strong>Carlo</strong> Opening Books for Amazons,” in Proc.<br />

Comput. and Games, LNCS 6515, Kanazawa, Japan, 2010, pp.<br />

124–135.<br />

[116] J. Kloetzer, H. Iida, and B. Bouzy, “The <strong>Monte</strong>-<strong>Carlo</strong> Approach<br />

in Amazons,” in Proc. Comput. Games Workshop, Amsterdam,<br />

Netherlands, 2007, pp. 113–124.<br />

[117] ——, “A Comparative Study <strong>of</strong> Solvers in Amazons Endgames,”<br />

in Proc. IEEE Conf. Comput. Intell. Games, Perth, Australia, 2008,<br />

pp. 378–384.<br />

[118] ——, “Playing Amazons Endgames,” Int. Comp. Games Assoc. J.,<br />

vol. 32, no. 3, pp. 140–148, 2009.<br />

[119] L. Kocsis and C. Szepesvári, “Bandit based <strong>Monte</strong>-<strong>Carlo</strong><br />

Planning,” in Euro. Conf. Mach. Learn. Berlin, Germany:<br />

Springer, 2006, pp. 282–293.<br />

[120] L. Kocsis, C. Szepesvári, and J. Willemson, “Improved <strong>Monte</strong>-<br />

<strong>Carlo</strong> <strong>Search</strong>,” Univ. Tartu, Estonia, Tech. Rep. 1, 2006.<br />

[121] S. Könnecke and J. Waldmann, “Efficient Playouts for the<br />

Havannah Abstract Board Game,” Hochschule Technik, Leipzig,<br />

Tech. Rep., 2009.<br />

[122] T. Kozelek, “<strong>Methods</strong> <strong>of</strong> MCTS and the game Arimaa,” M.S.<br />

thesis, Charles Univ., Prague, 2009.<br />

[123] K. L. Kroeker, “A New Benchmark for Artificial Intelligence,”<br />

Commun. ACM, vol. 54, no. 8, pp. 13–15, Aug. 2011.<br />

[124] * T. L. Lai and H. Robbins, “Asymptotically Efficient Adaptive<br />

Allocation Rules,” Adv. Appl. Math., vol. 6, pp. 4–22, 1985.<br />

[125] * M. Lanctot, K. Waugh, M. Zinkevich, and M. Bowling, “<strong>Monte</strong><br />

<strong>Carlo</strong> Sampling for Regret Minimization in Extensive Games,”<br />

in Proc. Adv. Neur. Inform. Process. Sys., Vancouver, Canada,<br />

2009, pp. 1078–1086.<br />

[126] * S. M. LaValle, “Rapidly-Exploring Random <strong>Tree</strong>s: A New<br />

Tool for Path Planning,” Iowa State Univ., Comp Sci. Dept., TR<br />

98-11, Tech. Rep., 1998.<br />

[127] C.-S. Lee, M. Müller, and O. Teytaud, “Guest Editorial: Special<br />

Issue on <strong>Monte</strong> <strong>Carlo</strong> Techniques and Computer Go,” IEEE<br />

Trans. Comp. Intell. AI Games, vol. 2, no. 4, pp. 225–228, Dec.<br />

2010.<br />

[128] C.-S. Lee, M.-H. Wang, G. M. J.-B. Chaslot, J.-B. Hoock,<br />

A. Rimmel, O. Teytaud, S.-R. Tsai, S.-C. Hsu, and T.-P. Hong,<br />

“The Computational Intelligence <strong>of</strong> MoGo Revealed in Taiwan’s<br />

Computer Go Tournaments,” IEEE Trans. Comp. Intell. AI Games,<br />

vol. 1, no. 1, pp. 73–89, 2009.<br />

[129] C.-S. Lee, M.-H. Wang, T.-P. Hong, G. M. J.-B. Chaslot, J.-B.<br />

Hoock, A. Rimmel, O. Teytaud, and Y.-H. Kuo, “A Novel<br />

Ontology for Computer Go Knowledge Management,” in Proc.<br />

IEEE Int. Conf. Fuzzy Sys., Jeju Island, Korea, Aug. 2009, pp.<br />

1056–1061.<br />

[130] J. R. Long, N. R. Sturtevant, M. Buro, and T. Furtak,<br />

“Understanding the Success <strong>of</strong> Perfect Information <strong>Monte</strong> <strong>Carlo</strong><br />

Sampling in Game <strong>Tree</strong> <strong>Search</strong>,” in Proc. Assoc. Adv. Artif. Intell.,<br />

Atlanta, Georgia, 2010, pp. 134–140.<br />

[131] * S. Lopez, “Rybka’s <strong>Monte</strong> <strong>Carlo</strong> analysis,” 2008. [Online].<br />

Available: http://www.chessbase.com/newsdetail.asp?newsid=<br />

5075<br />

[132] R. J. Lorentz, “Amazons Discover <strong>Monte</strong>-<strong>Carlo</strong>,” in Proc.<br />

Comput. and Games, LNCS 5131, Beijing, China, 2008, pp. 13–24.<br />

[133] ——, “Improving <strong>Monte</strong>-<strong>Carlo</strong> <strong>Tree</strong> <strong>Search</strong> in Havannah,” in<br />

Proc. Comput. and Games, LNCS 6515, Kanazawa, Japan, 2010,<br />

pp. 105–115.<br />

[134] ——, “Castro Wins Havannah Tournament,” Int. Comp. Games<br />

Assoc. J., vol. 33, no. 4, p. 232, 2011.<br />

[135] T. Mahlmann, J. Togelius, and G. N. Yannakakis, “Modelling<br />

and evaluation <strong>of</strong> complex scenarios with the Strategy Game<br />

Description Language,” in Proc. IEEE Conf. Comput. Intell. Games,<br />

Seoul, South Korea, 2011, pp. 174–181.<br />

[136] ——, “Towards Procedural Strategy Game Generation: Evolving<br />

Complementary Unit Types,” in Proc. Applicat. Evol. Comput.,<br />

LNCS 6624, Torino, Italy, 2011, pp. 93–102.<br />

[137] R. Maîtrepierre, J. Mary, and R. Munos, “Adaptive play in Texas<br />

Hold’em Poker,” in Proc. Euro. Conf. Artif. Intell., Patras, Greece,<br />

2008, pp. 458–462.<br />

[138] C. Mansley, A. Weinstein, and M. L. Littman, “Sample-Based<br />

Planning for Continuous Action Markov Decision Processes,”<br />

in Proc. 21st Int. Conf. Automat. Plan. Sched., Freiburg, Germany,<br />

2011, pp. 335–338.<br />

[139] L. S. Marcolino and H. Matsubara, “Multi-Agent <strong>Monte</strong> <strong>Carlo</strong><br />

Go,” in Proc. Int. Conf. Auton. Agents Multi. Sys., Taipei, Taiwan,<br />

2011, pp. 21–28.<br />

[140] S. Matsumoto, N. Hirosue, K. Itonaga, K. Yokoo, and<br />

H. Futahashi, “Evaluation <strong>of</strong> Simulation Strategy on Single-<br />

Player <strong>Monte</strong>-<strong>Carlo</strong> <strong>Tree</strong> <strong>Search</strong> and its Discussion for a<br />

Practical Scheduling Problem,” in Proc. Int. Multi Conf. Eng.<br />

Comput. Scientists, vol. 3, Hong Kong, 2010, pp. 2086–2091.<br />

[141] * R. E. McInerney, “Multi-Armed Bandit Bayesian Decision<br />

Making,” Univ. Oxford, Oxford, Tech. Rep., 2010.<br />

[142] J. Méhat and T. Cazenave, “Ary: A Program for General Game<br />

Playing,” Univ. Paris 8, Dept. Inform., Tech. Rep., 2008.<br />

[143] ——, “<strong>Monte</strong>-<strong>Carlo</strong> <strong>Tree</strong> <strong>Search</strong> for General Game Playing,”<br />

Univ. Paris 8, Dept. Info., Tech. Rep., 2008.<br />

[144] ——, “Combining UCT and Nested <strong>Monte</strong> <strong>Carlo</strong> <strong>Search</strong> for<br />

Single-Player General Game Playing,” IEEE Trans. Comp. Intell.<br />

AI Games, vol. 2, no. 4, pp. 271–277, 2010.<br />

[145] ——, “A Parallel General Game Player,” Künstliche Intelligenz,<br />

vol. 25, no. 1, pp. 43–47, 2011.<br />

[146] ——, “<strong>Tree</strong> Parallelization <strong>of</strong> Ary on a Cluster,” in Proc. Int. Joint<br />

Conf. Artif. Intell., Barcelona, Spain, 2011, pp. 39–43.<br />

[147] M. Möller, M. Schneider, M. Wegner, and T. Schaub, “Centurio, a<br />

General Game Player: Parallel, Java- and ASP-based,” Künstliche<br />

Intelligenz, vol. 25, no. 1, pp. 17–24, Dec. 2010.<br />

[148] M. Müller, “Fuego-GB Prototype at the Human machine competition<br />

in Barcelona 2010: a Tournament Report and Analysis,”<br />

Univ. Alberta, Edmonton, Tech. Rep., 2010.

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