S. Concepts and . .. Stacked-matrix-games, 115 5.2.1 Backward induction and Nash equilibria, p.115

H. Michael, R. J. Albert, D. Nowakowski, H. Wolfe-allis, M. P. Jaap-van-den-herik et al., Louis Victor Allis. A knowledge-based approach of connect-four the game is solved: White wins Master's thesis, Vrije Universitat Amsterdam The Netherlands [3] Louis Victor Allis Searching for Solutions in Games an Artificial Intelligence [4] Louis Victor Allis, M. van der Meulen, and H. Jaap van den Herik. Proof- Number Search Go- Moku solved by new search techniques Alternatingtime temporal logic Monte Carlo tree search in hex Solving hex: Beyond humans Finite-time analysis of the multiarmed bandit problem, Lessons in play: an introduction to combinatorial game theory. AK Peters Ltd H. Jaap van den Herik, Hiroyuki Iida, and Aske Plaat Computers and Games Nicoló Cesa-Bianchi, and Paul Fischer, pp.91-124, 1988.

D. Auger and O. Teytaud, THE FRONTIER OF DECIDABILITY IN PARTIALLY OBSERVABLE RECURSIVE GAMES, International Journal of Foundations of Computer Science, vol.23, issue.07, pp.1439-1450
DOI : 10.1142/S0129054112400576
URL : https://hal.archives-ouvertes.fr/hal-00710073

C. Baier and J. Katoen, Principles of model checking, 2008.

R. Balla and A. Fern, UCT for tactical assault planning in real-time strategy games, Boutilier [17], pp.40-45

W. Bruce and . Ballard, The *-minimax search procedure for trees containing chance nodes, Artificial Intelligence, vol.21, issue.3, pp.327-350, 1983.

P. Blackburn, M. De-rijke, and Y. Venema, Modal Logic Havannah and Twixt are PSPACE-complete On the complexity of trick-taking card games, 15] ´ Edouard Bonnet, Florian Jamain, and Abdallah Saffidine 8th International Conference on Computers and Games (CG). Yokohama, Japan 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2001.

M. Dennis, J. W. Breuker, and H. Uiterwijk, Jaap van den Herik. Solving 8×8 domineering, Theoretical Computer Science, vol.230, issue.1299, pp.195-206, 2000.

D. Michel-breuker, Memory versus Search in Games, 1998.

C. Browne, E. Powley, D. Whitehouse, S. Lucas, P. Cowling et al., A survey of Monte Carlo tree search methods. Computational Intelligence and AI in Games, IEEE Transactions on, vol.4, issue.1, pp.1-43, 2012.

M. Buro, Solving the Oshi-Zumo Game, 10th International Conference on Advances in Computer Games, Many Games, Many Challenges, pp.361-366, 2003.
DOI : 10.1007/978-0-387-35706-5_23

M. Buro, J. R. Long, T. Furtak, and N. R. Sturtevant, Improving state evaluation, inference, and search in trick-based card games

T. Cazenave, Abstract Proof Search, Lecture Notes in Computer Science, vol.2063, pp.39-54, 2000.
DOI : 10.1007/3-540-45579-5_3

T. Cazenave and R. J. Nowakowski, Retrograde analysis of woodpush, 2011.

T. Cazenave and A. Saffidine, Utilisation de la recherche arborescente Monte-Carlo au Hex, Revue d'intelligence artificielle, vol.23, issue.2-3, pp.183-202183, 2009.
DOI : 10.3166/ria.23.183-202

T. Cazenave and A. Saffidine, Score Bounded Monte-Carlo Tree Search, Computers and Games IEEE Symposium on Computational Intelligence and Games (CIG'08), pp.93-104, 1109.
DOI : 10.1007/978-3-642-17928-0_9

C. Chou, O. Teytaud, S. Cagnoni, C. Cotta, and M. Ebner, Revisiting Monte-Carlo Tree Search on a Normal Form Game: NoGo, Applications of Evolutionary Computation, pp.73-82, 2011.
DOI : 10.1007/978-3-642-20525-5_8
URL : https://hal.archives-ouvertes.fr/inria-00593154

D. Churchill and M. Buro, Build order optimization in starcraft, 7th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2011.

D. Churchill, A. Saffidine, and M. Buro, Fast heuristic search for RTS game combat scenarios, 8th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), pp.112-117, 2012.

E. M. Clarke, O. Grumberg, K. L. Mcmillan, and X. Zhao, Efficient generation of counterexamples and witnesses in symbolic model checking, Proceedings of the 32nd ACM/IEEE conference on Design automation conference , DAC '95, pp.427-432, 1995.
DOI : 10.1145/217474.217565

E. M. Clarke, Orna Grumberg, and Doron A. Peled. Model checking, 1999.

E. M. Clarke, S. Jha, Y. Lu, and H. Veith, Tree-like counterexamples in model checking, Proceedings 17th Annual IEEE Symposium on Logic in Computer Science, pp.19-29, 2002.
DOI : 10.1109/LICS.2002.1029814

R. Cleaveland, Tableau-based model checking in the propositional mu-calculus, Acta Informatica, vol.27, issue.8, pp.725-747, 1989.
DOI : 10.1007/BF00264284

A. Condon, The complexity of stochastic games Information and Computation, pp.203-224, 1992.

A. Condon, On algorithms for simple stochastic games Advances in computational complexity theory, pp.51-73, 1993.

L. Vítor-santos-costa, R. Damas, R. Reis, and . Azevedo, YAP Prolog user's manual, 2006.

A. Couëtoux, J. Hoock, N. Sokolovska, O. Teytaud, and N. Bonnard, Continuous Upper Confidence Trees, Learning and Intelligent Optimization, pp.433-445, 2011.
DOI : 10.1016/0196-8858(85)90002-8

A. Couëtoux, M. Milone, M. Brendel, H. Doghmen, M. Sebag et al., Continuous rapid action value estimates, 3rd Asian Conference on Machine Learning (ACML), pp.19-31, 2011.

R. Coulom, Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search, Computers and Games, pp.72-83, 2007.
DOI : 10.1007/978-3-540-75538-8_7
URL : https://hal.archives-ouvertes.fr/inria-00116992

R. Coulom, Computing Elo ratings of move patterns in the game of Go, ICGA Journal, vol.30, issue.4, pp.198-208, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00149859

E. Elkind, J. Lang, and A. Saffidine, Choosing collectively optimal sets of alternatives based on the Condorcet criterion, 22nd International Joint Conference on Artificial Intelligence (IJCAI), pp.186-191, 2011.

K. Etessami and M. Yannakakis, Recursive Markov Decision Processes and Recursive Stochastic Games, 32nd International Colloquium on Automata, Languages and Programming (ICALP), pp.891-903, 2005.
DOI : 10.1007/11523468_72

H. Everett, Recursive games. Contributions to the Theory of Games III, pp.47-78, 1957.

H. Finnsson and Y. Björnsson, Simulation-based approach to general game playing, 23rd AAAI Conference on Artificial Intelligence, pp.259-264, 2008.

M. Fox and D. Long, Pddl2.1: An extension to pddl for expressing temporal planning domains, Journal of Artificial Intelligence Research (JAIR), vol.20, pp.61-124, 2003.

S. Aviezri, D. Fraenkel, and . Lichtenstein, Computing a perfect strategy for n × n Chess requires time exponential in n, Journal of Combinatorial Theory, Series A, vol.31, issue.2, pp.199-214, 1981.

S. Aviezri, M. R. Fraenkel, D. S. Garey, T. J. Johnson, Y. Schaefer et al., The complexity of checkers on an n × n board, 19th Annual Symposium on Foundations of Computer Science, pp.55-64, 1978.

I. Frank and D. Basin, Search in games with incomplete information: a case study using Bridge card play, Artificial Intelligence, vol.100, issue.1-2, pp.87-123, 1998.
DOI : 10.1016/S0004-3702(97)00082-9

T. Furtak and M. Buro, On the complexity of two-player attrition games played on graphs, 6th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2010.

T. Furtak, M. Kiyomi, T. Uno, and M. Buro, Generalized Amazons is PSPACE-complete, 19th International Joint Conference on Artificial Intelligence (IJCAI-05), pp.5-132, 2005.

S. Gelly and D. Silver, Achieving master level play in 9 × 9 computer Go, 23rd national conference on Artifical Intelligence (AAAI'08), pp.1537-1540, 2008.

M. Genesereth and N. Love, General Game Playing, Synthesis Lectures on Artificial Intelligence and Machine Learning, vol.8, issue.2, pp.62-72, 2005.
DOI : 10.2200/S00564ED1V01Y201311AIM024

A. Gilpin and T. Sandholm, Lossless abstraction of imperfect information games, Journal of the ACM, vol.54, issue.5, 2007.
DOI : 10.1145/1284320.1284324

L. Matthew and . Ginsberg, GIB: Imperfect information in a computationally challenging game, Journal of Artificial Intelligence Research, vol.14, pp.303-358, 2001.

V. Goranko and G. Van-drimmelen, Complete axiomatization and decidability of Alternating-time temporal logic, Theoretical Computer Science, vol.353, issue.1-3, pp.93-117, 2006.
DOI : 10.1016/j.tcs.2005.07.043

A. Groce and W. Visser, What went wrong: Explaining counterexamples . Model Checking Software, pp.121-136, 2003.

E. Peter, N. J. Hart, B. R. Nilsson, M. Buro, and J. Schaeffer, A formal basis for the heuristic determination of minimum cost paths Rediscovering *-minimax search, H. Jaap van den Herik Computers and Games, pp.100-107, 1968.

R. A. Hearn, Games, Puzzles, and Computation, 2006.

A. Heifets and I. Jurisica, Construction of new medicines via game proof search, pp.1564-1570

J. Hoffmann and S. Edelkamp, The deterministic part of ipc-4: An overview, Journal of Artificial Intelligence Research, vol.24, pp.519-579, 2005.

J. Gerard and . Holzmann, Design and Validation of Computer Protocols, 1991.

J. Gerard and . Holzmann, The model checker SPIN, IEEE Transactions on Software Engineering, vol.23, issue.5, pp.279-295, 1997.

H. Horacek, Towards understanding conceptual differences between minimaxing and product-propagation, 14th European Conference on Artificial Intelligence (ECAI), pp.604-608, 2000.

H. Horacek and H. Kaindl, An analysis of decision quality of minimaxing vs. product propagation, 2009 IEEE International Conference on Systems, Man and Cybernetics, pp.2568-2574, 2009.
DOI : 10.1109/ICSMC.2009.5346327

S. Iwata and T. Kasai, The Othello game on an n ?? n board is PSPACE-complete, Theoretical Computer Science, vol.123, issue.2, pp.329-340, 1994.
DOI : 10.1016/0304-3975(94)90131-7

M. J. Kearns, Y. Mansour, and A. Y. Ng, A sparse sampling algorithm for near-optimal planning in large Markov Decision Processes

A. Kishimoto and M. Müller, A solution to the GHI problem for depth-first proof-number search, Information Sciences, vol.175, issue.4, pp.296-314, 2005.
DOI : 10.1016/j.ins.2004.04.012

A. Kishimoto, M. H. Winands, M. Müller, and J. Saito, Game-Tree Search Using Proof Numbers: The First Twenty Years, ICGA Journal, vol.35, issue.3, pp.131-156, 2012.
DOI : 10.3233/ICG-2012-35302

E. Donald, R. W. Knuth, and . Moore, An analysis of alpha-beta pruning, Artificial Intelligence, vol.6, issue.4, pp.293-326, 1975.

L. Kocsis and C. Szepesvàri, Bandit Based Monte-Carlo Planning, 17th European Conference on Machine Learning, pp.282-293, 2006.
DOI : 10.1007/11871842_29

D. Koller and N. Megiddo, Fast algorithms for finding randomized strategies in game trees, Proceedings of the twenty-sixth annual ACM symposium on Theory of computing , STOC '94, pp.750-759, 1994.
DOI : 10.1145/195058.195451

R. E. Korf, Depth-first iterative-deepening, Artificial Intelligence, vol.27, issue.1, pp.97-109, 1985.
DOI : 10.1016/0004-3702(85)90084-0

A. Kovarsky and M. Buro, Heuristic Search Applied to Abstract Combat Games, Canadian Conference on AI, pp.66-78, 2005.
DOI : 10.1007/11424918_9

S. Kupferschmid and M. Helmert, A Skat Player Based on Monte-Carlo Simulation, Computers and Games, pp.135-147, 2006.
DOI : 10.1007/978-3-540-75538-8_12

L. Kurzen, Complexity in Interaction, 2011.

M. Lachmann, C. Moore, and I. Rapaport, Who wins domineering on rectangular boards, pp.307-315, 2002.

M. Lanctot, A. Saffidine, J. Veness, C. Archibald, and M. Winands, Monte carlo *-minimax search, 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013.

M. Lange, Model checking propositional dynamic logic with all extras, Journal of Applied Logic, vol.4, issue.1, pp.39-49, 2006.
DOI : 10.1016/j.jal.2005.08.002

C. Lee, M. Wang, G. Chaslot, J. Hoock, A. Rimmel et al., The computational intelligence of MoGo revealed in Taiwan's computer Go tournaments, IEEE Transactions on Computational Intelligence and AI in Games, vol.1, issue.1, pp.73-89, 2009.

C. Lee, M. Müller, and O. Teytaud, Special Issue on Monte Carlo Techniques and Computer Go, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.225-228, 2010.
DOI : 10.1109/TCIAIG.2010.2099154

X. Leroy, Formal verification of a realistic compiler, Communications of the ACM, vol.52, issue.7, pp.107-115, 2009.
DOI : 10.1145/1538788.1538814
URL : https://hal.archives-ouvertes.fr/inria-00415861

N. L. David and . Levy, The million pound Bridge program In Heuristic Programming in Artificial Intelligence: The First Computer Olympiad, pp.95-103, 1989.

A. Yanhong, S. D. Liu, and . Stoller, From datalog rules to efficient programs with time and space guarantees, ACM Transactions on Programming Languages and Systems, issue.6, pp.311-349, 2009.

A. Lomuscio, H. Qu, and F. Raimondi, MCMAS: A Model Checker for the Verification of Multi-Agent Systems, Computer Aided Verification, pp.682-688, 2009.
DOI : 10.1007/978-3-642-02658-4_55

J. Long, N. R. Sturtevant, M. Buro, and T. Furtak, Understanding the success of perfect information Monte Carlo sampling in game tree search, 24th AAAI Conference on Artificial Intelligence (AAAI), pp.134-140, 2010.

R. J. Lorentz, Amazons Discover Monte-Carlo, Computers and Games, pp.13-24, 2008.
DOI : 10.1007/978-3-540-87608-3_2

N. C. Love, T. L. Hinrichs, and M. R. Genesereth, General Game Playing: Game Description Language specification, 2006.

M. Lustrek, M. Gams, and I. Bratko, A program for playing tarok, ICGA Journal, vol.26, issue.3, pp.190-197, 2003.

L. Soriano-marcolino, A. X. Jiang, and M. Tambe, Multiagent team formation-diversity beats strength, 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013.

S. Marlow and S. P. Jones, The Glasgow Haskell Compiler In The Architecture of Open Source Applications

A. David and . Mcallester, Conspiracy numbers for min-max search, Artificial Intelligence, vol.35, issue.3, pp.287-310, 1988.

C. Moldenhauer, Game tree search algorithms for the game of cops and robber, 2009.

H. Moulin, Axioms of cooperative decision making, 1991.
DOI : 10.1017/CCOL0521360552

M. Müller, Proof-Set Search, Computers and Games, pp.88-107, 2002.
DOI : 10.1007/978-3-540-40031-8_7

M. Möller, M. Schneider, M. Wegner, and T. Schaub, Centurio, a General Game Player: Parallel, Java- and ASP-based, KI - K??nstliche Intelligenz, vol.26, issue.2
DOI : 10.1007/s13218-010-0077-4

M. Müller, Computer Go, Artificial Intelligence, vol.134, issue.1-2, pp.145-179, 2002.
DOI : 10.1016/S0004-3702(01)00121-7

A. Nagai, Df-pn algorithm for searching AND/OR trees and its applications, 2001.

E. V. Nalimov, G. M. Haworth, and E. A. Heinz, Spaceefficient indexing of chess endgame tables, ICGA Journal, vol.23, issue.3, pp.148-162, 2000.

J. A. Nijssen and M. H. Winands, Enhancements for Multi-Player Monte-Carlo Tree Search, H. van den Herik, Hiroyuki Iida, and Aske Plaat Computers and Games, pp.238-249, 2011.
DOI : 10.1007/978-3-642-17928-0_22

J. A. Nijssen and M. H. Winands, An overview of search techniques in multi-player games, Computer Games Workshop at ECAI 2012, pp.50-61, 2012.

T. Obata, T. Sugiyama, K. Hoki, and T. Ito, Consultation Algorithm for Computer Shogi: Move Decisions by Majority, H.Jaap van den Herik, Hiroyuki Iida, and Aske Plaat Computers and Games, pp.156-165, 2011.
DOI : 10.1007/978-3-642-17928-0_15

J. Orkin, Three states and a plan: the AI of FEAR, Game Developers Conference, 2006.

J. Pawlewicz and ?. Lew, Improving Depth-First PN-Search: 1???+????? Trick, 5th international conference on Computers and Games, pp.160-171, 2006.
DOI : 10.1007/978-3-540-75538-8_14

J. Pearl, On the nature of pathology in game searching, Artificial Intelligence, vol.20, issue.4, pp.427-453, 1983.
DOI : 10.1016/0004-3702(83)90004-8

J. Pearl, Heuristics: intelligent search strategies for computer problem solving, 1984.

R. Polikar, Ensemble based systems in decision making, IEEE Circuits and Systems Magazine, vol.6, issue.3, pp.21-451688199, 2006.
DOI : 10.1109/MCAS.2006.1688199

S. Reisch, Hex is PSPACE-complete, Acta Informatica, vol.16, issue.2, pp.167-191, 1981.
DOI : 10.1007/BF00288964

A. Rimmel, O. Teytaud, C. Lee, M. Shi-jim-yen, S. Wang et al., Current Frontiers in Computer Go, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.229-238, 2010.
DOI : 10.1109/TCIAIG.2010.2098876
URL : https://hal.archives-ouvertes.fr/inria-00544622

J. Michael-robson, The complexity of Go, IFIP, pp.413-417, 1983.

W. John, H. E. Romein, and . Bal, Solving Awari with parallel retrograde analysis, Computer, vol.36, issue.10, pp.26-33, 2003.

M. Sheldon and . Ross, Goofspiel: The game of pure strategy, Journal of Applied Probability, vol.8, issue.3, pp.621-625, 1971.

J. Stuart, P. Russell, and . Norvig, Artificial Intelligence ? A Modern Approach. Pearson Education, 2010.

A. Saffidine, The Game Description Language Is Turing Complete, IEEE Transactions on Computational Intelligence and AI in Games, vol.6, issue.4, 2013.
DOI : 10.1109/TCIAIG.2014.2354417

A. Saffidine and T. Cazenave, A forward chaining based game description language compiler, IJCAI Workshop on General Intelligence in Game-Playing Agents (GIGA), pp.69-75, 2011.

A. Saffidine and T. Cazenave, A general multi-agent modal logic K framework for game tree search, Computer Games Workshop @ ECAI, 2012.

A. Saffidine and T. Cazenave, Multiple-outcome proof number search, 20th European Conference on Artificial Intelligence (ECAI), pp.708-713, 2012.

A. Saffidine and T. Cazenave, Developments on Product Propagation, 8th International Conference on Computers and Games (CG), 2013.
DOI : 10.1007/978-3-319-09165-5_9
URL : https://hal.archives-ouvertes.fr/hal-01497372

A. Saffidine, T. Cazenave, and J. Méhat, UCD: Upper Confidence bound for rooted Directed acyclic graphs. Knowledge-Based Systems, pp.26-33, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01499672

A. Saffidine, N. Jouandeau, and T. Cazenave, Solving breakthrough with Race Patterns and Job-Level Proof Number Search, H. van den Herik and Aske Plaat Advances in Computer Games, pp.196-207
DOI : 10.1007/978-3-642-31866-5_17
URL : https://hal.archives-ouvertes.fr/hal-01499675

A. Saffidine, H. Finnsson, and M. Buro, Alpha-beta pruning for games with simultaneous moves, pp.556-562

A. Saffidine, N. Jouandeau, C. Buron, and T. Cazenave, Material Symmetry to Partition Endgame Tables, 8th International Conference on Computers and Games (CG), 2013.
DOI : 10.1007/978-3-319-09165-5_16
URL : https://hal.archives-ouvertes.fr/hal-01497383

J. Saito and M. H. Winands, Paranoid Proof-Number Search, Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, pp.203-210, 2010.
DOI : 10.1109/ITW.2010.5593354

P. D. Maarten, M. H. Schadd, and . Winands, Best reply search for multiplayer games, IEEE Transactions Computational Intelligence and AI in Games, vol.3, issue.1, pp.57-66, 2011.

P. D. Maarten, M. H. Schadd, J. W. Winands, H. Uiterwijk, M. H. Jaap-van-den-herik et al., Best play in Fanorona leads to draw, New Mathematics and Natural Computation, vol.4, issue.3, pp.369-387, 2008.

P. D. Maarten, M. H. Schadd, H. Winands, G. M. Jaap-van-den-herik, J. W. Chaslot et al., Single-player Monte-Carlo tree search, Computers and Games, pp.1-12, 2008.

J. Schaeffer, Conspiracy numbers, Artificial Intelligence, vol.43, issue.1, pp.67-84, 1990.
DOI : 10.1016/0004-3702(90)90071-7

J. Schaeffer, A. Plaat, and A. Junghanns, Unifying singleagent and two-player search, Information Sciences, vol.135, issue.01, pp.3-4151, 2001.

J. Schaeffer, Y. Björnsson, N. Burch, R. Lake, P. Lu et al., Building the Checkers 10-Piece Endgame Databases, Advances in Computer Games 10, pp.193-210, 2003.
DOI : 10.1007/978-0-387-35706-5_13

J. Schaeffer, Y. Björnsson, N. Burch, A. Kishimoto, M. Müller et al., Solving checkers, IJCAI, pp.292-297, 2005.

J. Schaeffer, N. Burch, Y. Björnsson, A. Kishimoto, M. Müller et al., Checkers Is Solved, Science, vol.317, issue.5844, p.3171518, 2007.
DOI : 10.1126/science.1144079

S. Schiffel and M. Thielscher, A Multiagent Semantics for the Game Description Language, Agents and Artificial Intelligence Communications in Computer and Information Science, vol.67, pp.44-55, 2010.
DOI : 10.1007/978-3-642-11819-7_4

M. Schijf, L. Victor-allis, and J. W. Uiterwijk, Proof-number search and transpositions, ICCA Journal, vol.17, issue.2, pp.63-74, 1994.

M. Schofield and A. Saffidine, High speed forward chaining for general game playing, IJCAI Workshop on General Intelligence in Game-Playing Agents (GIGA), 2013.

M. Seo, H. Iida, and J. W. Uiterwijk, The PN???-search algorithm: Application to tsume-shogi, Artificial Intelligence, vol.129, issue.1-2, pp.253-277, 2001.
DOI : 10.1016/S0004-3702(01)00084-4

M. Shafiei, N. R. Sturtevant, and J. Schaeffer, Comparing UCT versus CFR in simultaneous games, IJCAI-09 Workshop on General Game Playing (GIGA'09), pp.75-82, 2009.

Y. Shoham and K. Leyton-brown, Multiagent systems: Algorithmic, game-theoretic, and logical foundations, 2009.
DOI : 10.1017/CBO9780511811654

R. James, P. Slagle, and . Bursky, Experiments with a multipurpose, theorem-proving heuristic program, Journal of the ACM, vol.15, issue.1, pp.85-99, 1968.

S. Soeda, T. Kaneko, and T. Tanaka, Dual Lambda Search and Shogi Endgames, H. van den Herik Advances in Computer Games, pp.126-139, 2006.
DOI : 10.1007/11922155_10

D. Stern, R. Herbrich, and T. Graepel, Learning to solve game trees, Proceedings of the 24th international conference on Machine learning, ICML '07, pp.839-846, 2007.
DOI : 10.1145/1273496.1273602

R. Nathan and . Sturtevant, Last-branch and speculative pruning algorithms for max n, 18th International Joint Conference on Artificial Intelligence (IJCAI), pp.669-678, 2003.

R. Nathan and . Sturtevant, Leaf-value tables for pruning non-zero-sum games, 19th International Joint Conference on Artificial Intelligence (IJCAI- 05), pp.317-323, 2005.

R. Nathan, R. E. Sturtevant, and . Korf, On pruning techniques for multi-player games, 17th National Conference on Artificial Intelligence and 12th Conference on Innovative Applications of Artificial Intelligence, AAAI/IAAI 2000, pp.201-207, 2000.

R. Nathan, A. M. Sturtevant, and . White, Feature construction for reinforcement learning in Hearts, Computers and Games, pp.122-134, 2006.

M. Thielscher, Answer Set Programming for Single-Player Games in General Game Playing, ICLP, pp.327-341, 2009.
DOI : 10.1007/3-540-46767-X_23

K. Thompson, 6-piece endgames [153] Thomas Thomsen. Lambda-search in game trees -with application to Go, ICCA Journal ICGA Journal, vol.19, issue.234, pp.215-226203, 1996.

J. D. Ullmann, An Algorithm for Subgraph Isomorphism, Journal of the ACM, vol.23, issue.1, pp.31-42, 1976.
DOI : 10.1145/321921.321925

H. Jaap-van-den, M. H. Herik, and . Winands, Proof-Number Search and its variants, Oppositional Concepts in Computational Intelligence, pp.91-118, 2008.

H. Jaap-van-den-herik, J. W. Uiterwijk, and J. Van-rijswijck, Games solved: Now and in the future, Artificial Intelligence, vol.134, issue.1-2, pp.277-311, 2002.
DOI : 10.1016/S0004-3702(01)00152-7

M. Wiebe-van-der-hoek and . Pauly, Modal logic for games and information . Handbook of modal logic, pp.1077-1148, 2006.

M. Wiebe-van-der-hoek and . Wooldridge, Model Checking Knowledge and Time, Model Checking Software, pp.25-26, 2002.
DOI : 10.1007/3-540-46017-9_9

M. Wiebe-van-der-hoek and . Wooldridge, Cooperation, knowledge, and time: Alternating-time temporal epistemic logic and its applications, Studia Logica, vol.75, issue.1, pp.125-157, 2003.
DOI : 10.1023/A:1026185103185

J. Hans-van-ditmarsch, A. Lang, and . Saffidine, Strategic voting and the logic of knowledge, 14th conference on Theoretical Aspects of Rationality and Knowledge (TARK), pp.196-205, 2013.

P. Hans, . Van-ditmarsch, B. P. Wiebe-van-der-hoek, and . Kooi, Concurrent dynamic epistemic logic for MAS, 2nd international joint conference on Autonomous agents and multiagent systems, pp.201-208, 2003.

J. Van and R. , Search and evaluation in Hex, 2002.

J. Wästlund, A solution of two-person single-suit Whist, The Electronic Journal of Combinatorics, vol.12, issue.1, p.43, 2005.

J. Wästlund, Two-person symmetric Whist, The Electronic Journal of Combinatorics, vol.12, issue.1, p.44, 2005.

H. M. Mark, Y. Winands, J. Björnsson, and . Saito, Monte- Carlo tree search solver, H. Jaap van den Herik Computers and Games, pp.25-36, 2008.

H. M. Mark, Y. Winands, J. Björnsson, and . Saito, Monte Carlo tree search in lines of action, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.239-250, 2010.

M. Wooldridge, T. Agotnes, P. E. Dunne, and W. Van-der-hoek, Logic for automated mechanism design ? a progress report, National Conference on Artificial Intelligence (AAAI-07), 1999.

I. Wu, H. Lin, D. Sun, . Kuo-yuan, P. Kao et al., Job-level proof number search, IEEE Transactions on Computational Intelligence and AI in Games, vol.5, issue.1, pp.44-56, 2013.

K. Yoshizoe, A. Kishimoto, and M. Müller, Lambda Depth- First Proof Number Search and its application to Go, 20th International Joint Conference on Artificial Intelligence (IJCAI), pp.2404-2409, 2007.