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Marsland, T., Breitkreutz, T. and Sutphen, S. (1991). A Network Multiprocessor for Experiments in Parallelism. Concurrency: Practice and Experience, Vol. 3, No. 3, pp. 203 219.
Marsland, T.A. (1992). Chess and AI: Workshop Report. ICCA Journal, Vol. 15, No. 4, pp. 228-229. ISSN 0920-234X.
Marsland, T.A. (1992). Computer Chess and Search. Encyclopedia of Artificial Intelligence (2nd ed.) (ed. S.C. Shapiro) pp. 224-241. John Wiley & Sons, Inc., New York, NY. ISBN 0-471-50305-3.
Marsland, T. (1993). Single_Agent and Game Tree Search. Encyclopedia of Computer Science and Technology, Vol 27, No. 12, pp. 317 335.
Marsland, T.A. and Gao, Y. (1995). Speculative Parallelism Improves Search? Technical Report 95-05, Department of Computing Science, University of Alberta, Edmonton, Alberta.
Marsland, T.A. (1997). A Report on the Fredkin Prize for Computer Chess. ICCA Journal, Vol. 20, No. 3, pp. 206-207.
Marsland, T.A. and Björnsson, Y. (2000). From Minimax to Manhattan. Games in AI Research (eds. H.J. van den Herik and H. Iida), pp. 5-17. Universiteit Maastricht, Maastricht, The Netherlands. ISBN 90-621-6416-1.
Marlsand, T.A. and Bjornsson, Y. (2001). Variable-Depth Search. Advances in Computer Games 9 (eds. H.J. van den Herik and B. Monien), pp. 9-24. IKAT, Universiteit Maastricht, Maastricht, The Netherlands. ISBN 90-6216-5761 / 90-6216-5664.
Marsland, T.A. (2002). Personal communication.
Matanovic, A. (ed.) (1974). The Encyclopedia of Chess Openings. B.T. Batsford Limited, London, UK.
Matanovic, A. (ed.) (1977). Encyclopaedia of chess openings. D. 27, 6. Batsford/Šahovski Informator, Beograd.
Matanović, A. (1980). The Encyclopaedia of Chess Middlegames, Combinations. Chess Informant, Beograd, Yugoslavia.
Matanovic, A. et al. (1980). Šahovsik Informator 29. Game 153. Centar za unapredivaje šaha. Beograd, Yugoslavia.
Matanovic, A. (ed.) (1986). Encyclopaedia of Chess Endings, Rook Endings II. Šahovski Informator, Beograd.
Matanović, A. (1986). The Encyclopaedia of Chess Endings. Vol. 3, Rooks. Chess Informant, Beograd, Yugoslavia.
Matanovic, A. (ed.) (1988). Šahovski informator 44. Šahovski Informator, Beograd, Yugoslavia.
Matheus, C.J. (1989). A Constructive Induction Framework. Proceedings of the 6th International Workshop on Machine Learning (ed. A.M. Segre), pp. 474 475. Morgan Kaufmann, Los Altos, CA.
Mathworld (2006). http://mathworld.wolfram.com/QuarticEquation.html.
Matsubara, H., Handa, H., and Motoyoshi, F. (1991). An Attempt at Automatic evaluation of Tsume Shogi (Japanese Chess mating problem). ETL technical report, ETL TR 91 43, Electrotechnical Laboratory, Japan.
Matsubara, H. (1993). Shogi (Japanese Chess) as the AI research target next to chess. Electrotechnical Laboratory Technical Report, ETL TR 93 23, Tsukuba.
Matsubara, H. and Handa, K. (1994). Some Properties of Shogi as a Game. Proceedings of Artificial Intelligence, Vol. 96, No. 3, pp. 21-30. Information Processing Society of Japan. (In Japanese).
Matsubara, H., Iida, H., and Grimbergen, R. (1996). Natural Developments in Game Research: from Chess to Shogi to Go. ICCA Journal, Vol. 19, No. 2, pp. 103-113. ISSN 0920-234X.
Matsubara, H., Iida, H., and Uiterwijk, J.W.H.M. (1996). A Shogi-Computer Test Set. Proceedings of the 1996 ACM Computer Science Conference, pp. 139-146. ACM, New York, N.Y.
Matsubara, H. and Grimbergen, R. (1997). Differences between shogi and western chess from a computational point of view. International Colloquium on Board Games in Academia 2.
Matsubara, H. and Iida, H. (1998). Evaluation of Computer Shogi by Next-Move Test (no. 1). Advances in Computer Shogi 2, pp. 61-111. Kyoritsu Publisher. In Japanese.
Matsubara, H. (2001). Evaluation of Computer Shogi by Next-Move Test (no. 2). IPSJ SIG Notes, Vol. 2001, No. 28, pp. 39-46. In Japanese.
Matsumoto, M. and Nishimura, T. (1998). Mersenne twister: A 623-dimensionally equidistributed uniformpseudo-random number generator. ACMTMCS: ACM Transactions on Modeling and Computer Simulation,Vol. 8, pp. 3.30.
Mattison, H. (1918). Deutsches Wochenschach. #23 in Sutherland and Lommer (1938).

Maunders, M.E. (1904). Monthly Notices of the Royal Astronomical Society, Vol. LXIV, pp. 747-761.


Mayer, S.P. (2001). Theorem on Endless Moves. Appendix to Wernham (2001).

See http://us.share.geocities.com/omweso/board_games_in_academia_v_omweso.pdf.


McAllester, D.A. (1985). A New Procedure for Growing Minimax Trees. Technical Report, Artificial Intelligence Laboratory, MIT.
McAllester, D.A. (1988). Conspiracy Numbers for Min-Max Search. Artificial Intelligence, Vol. 35, No. 1, pp. 287-310. ISSN 0004-3702.
McAllester, D.A. and Yuret, D. (1993). Alpha-beta-conspiracy search. URL: http://www.research.att.com/~dmac/abc.ps.
McCarthy, J. (1983). Some Expert Systems Need Common Sense.
McCarthy, J. (1989). The Fruitfly on the Fly. ICCA Journal, Vol. 12, No. 4, pp. 199-206. ISSN 0920-234X.
McCarthy, J. (1990). Chess as the Drosophila of AI. Computers, Chess, and Cognition (eds. T.A. Marsland and J. Schaeffer), pp. 227-237. Springer-Verlag, New York. ISBN 0-387-97415-6.
McCarthy, J. and Feigenbaum, E. (1991). In Memoriam. Arthur L. Samuel: Pioneer in Machine Learning. ICCA Journal, Vol. 14, No. 1, pp. 19-20. ISSN 0920-234X.
McCarthy, J. (1997). AI as Sport. Science, Vol. 276, June 6, pp. 1518-1519.
McCorduck, P. (1979). Machines Who Think. W.H. Freeman and Company, San Francisco.
McDowell, M. (2005). Fairy Chess. The British Chess Problem Society Website. Available at: http://www.bcps.knightsfield.co.uk/fairies.html.
Mead, C. and Ismail, M. (ed.) (1989). Analog VLSI Implementation of Neural Systems. Kluwer Academic Press, Boston, MA.
Mednis, E. (1989). The 50-Move Rule Adapted (1). ICCA Journal, Vol. 12, No. 2, p. 123.
Mednis, E. (1991). Database Results for KQKRN and KQKRB Annotated. ICCA Journal, Vol. 14, No. 2, pp. 66-70. ISSN 0920-234X.
Mednis, E. (1996). Advanced Endgame Strategies, esp. 94-96. Chess Enterprises. ISBN 0-9454-7059-2.

Mehlsam, G. (1989). Automatisches Erzeugen von Klassifikationskriterien. Dissertation, Technische Universität Wien.


Mehlsam, G., Kaindl, H. and Barth, W. (1991). Feature Construction During Tree Learning. Procee­dings GWAI.
Menezes, A.J., Oorschot, P.C. van, and Vanstone, S.A. (1997). Handbook of applied cryptography. CRC Press, Boca Raton, Florida. ISBN 0849385237.
Mertes, H. (1975). Problemschach und Computer. Die Wiesbadener Problemschachtage, Feenschach Sonderdruck, pp. 37 41.
Messerschmidt, H.J. (1980). Parallel Programming for a Chess Endgame Data-Base. Software - Practice and Experience, Vol. 10, pp. 475-487.
Messom, C.H. (1992). Engineering Reliable Neural Networks. Ph.D. thesis, Loughborough University, UK.
Meulen, M. van der (1988). Parallel Conspiracy-Number Search. M.Sc. thesis, Vrije Universiteit. Faculty of Mathematics and Computer Science, Vrije Universiteit, Amsterdam.
Meulen, M. van der (1989). Weight Assessment in Evaluation Functions. Advances in Computer Chess 5 (ed. D.F. Beal), pp. 81 89. North-Holland, Amsterdam. ISBN 0 444 87159 4.
Meulen, M. van der (1990). Conspiracy-Number Search. ICCA Journal, Vol. 13, No. 1, pp. 3-14. ISSN 0920-234X.
Meulen, M. van der, Allis, L.V. and Herik, H.J. van den (1990). A Comment on `Conspiracy-Number Search'. ICCA Journal, Vol. 13, No. 2, pp. 74-75. ISSN 0920-234X.
Meulen, M. van der, Allis, L.V. and Herik, H.J. van den (1990). Lithidion: an Awari playing Program. Technical Reports in Computer Science. Report 90 05. University of Limburg, The Netherlands. ISSN 0922 8721.
Meyer-Kahlen, S. and Huber, R. (2004). Universal Chess Interface (UCI) Protocol. http://www.chessbase.com/download/index.asp?cat=UCI%2DEngines.
Meyer-Kahlen, S. (2005). Deep Shredder. http://www.shredderchess.com/shredderdeep.html.
Michalski, R. and Negri, P. (1977). An Experiment on Inductive Learning in Chess Endgames. Machine Learning 8 (eds. E.W. Elcock and D. Michie), pp. 175-192. Edinburgh University Press, Edinburgh.
Michalski, R.S. and Winston, P.H. (1986). Variable Precision Logic. Artificial Intelligence, Vol. 29, pp. 121-146.
Michie, D. (1976). An Advice-Taking System for Computer Chess. Computer Bulletin, Ser. 2, Vol. 10, pp. 12-14. ISSN 0010-4531.
Michie, D. (1977). King and Rook Against King: Historical Background and a Problem on the Infinite Board. Advances in Computer Chess 1 (ed. M.R.B. Clarke), pp. 30-59. Edinburgh University Press, Edinburgh. ISBN 0-85224-292-1.
Michie, D. and Bratko, I. (1978). Advice Table Representations of Chess End-Game Knowledge. Proceedings 3rd AISB/GI Conference, pp. 194-200.
Michie, D. (1980). Chess with Computers. Interdisciplinary Science Reviews. Vol. 5, No. 3, pp. 215-227. ISSN 0308-0188.
Michie, D. (1981). A Theory of Evaluative Comments in Chess with a Note on Minimaxing. The Computer Journal, Vol. 24, No. 3, pp. 278-286.
Michie, D. (1982). Chess with computers. Machine Intelligence and Related Topics. Gordon and Breach Science Publishers.
Michie, D. (1986). The superarticulacy phenomenon in the context of software manufacture. Proc. Roy. Soc. (A).
Michie, D. (1986). Towards a Knowledge Accelerator. Advances in Computer Chess 4 (ed. D. Beal), pp. 1 7. Pergamon Press, Oxford. ISBN 0-08-029763-3.
Michie, D. and Hayes-Michie, J. (1986). Semi-automatic methods of knowledge enhancement (Research Report). Intelligent Terminals Limited, Glasgow.
Michie, D. (1987). Current Development in Expert Systems. Applications of Expert Systems (ed. J.R. Quinlan), pp. 137-156. Turing Institute Press in association with Addison-Wesley Company, Sidney, Australia. ISBN 0-201-17449-9.
Michie, D. and Bratko, I. (1987). Ideas on Knowledge Synthesis Stemming from the KBBKN Endgame. ICCA Journal, Vol. 10, No. 1, pp. 3 13. ISSN 0920-234X.
Michie, D. and Bratko, I. (1987). Ideas on Knowledge Synthesis ..... a Correction. ICCA Journal, Vol. 10, No. 2, p. 94. ISSN 0920-234X.
Michie, D. (1989). Brute Force in Chess and Science. ICCA Journal, Vol. 12, No. 3, pp. 127-143. ISSN 0920-234X.
Michie, D. (1990). Brute Force in Chess and Science. Computers, Chess, and Cognition (eds. T.A. Marsland and J. Schaeffer), pp. 239-257. Springer-Verlag, New York. ISBN 0-387-97415-6.
Michie, D. and Bratko, I. (1991). Comments to `Chunking for Experience'. ICCA Journal, Vol. 14, No. 1, p. 18. ISSN 0920-234X.
Mihatsch, O. and Neuneier, R. (2002). Risk-Sensitive Reinforcement Learning. Machine Learning, Vol. 49, pp. 267-290. ISSN 0885-6125.
Milgram, S. (1967). The Small World Problem. Psychology Today, Vol. 1, pp. 62-72.
Miller, G.A. (1956). The Magical Number Seven, Plus or Minus Two: Some Limits On Our Capacity For Processing Information. Psychological Review, No. 63, pp. 81-97.
Miller, ,R.C. (1995). A Type-Checking Preprocessor for Cilk 2, a Multithreaded C Language. Master’s Thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA.
Milner, S.D. and Walker, A.N. (1997). Heuristics and Loops in KQKR. Advances in Computer Chess 8 (eds. H.J. van den Herik and J.W.H.M. Uiterwijk), pp. 45-52. Universiteit Maastricht, Maastricht, The Netherlands. ISBN 90-6216-2347.
Minsky, M.L. and Papert, S.A. (1969). Perceptrons, An Introduction to Computational Geometry. MIT Press, Cambridge, MA. Expanded edition (1988), MIT Press, Cambridge, MA. ISBN 0-262-63111-3.
Minsky, M. L. and Papert, S.A. (1988). Perceptrons, An Introduction to Computational Geometry. Expanded edition. MIT Press, Cambridge, MA, USA. ISBN 0-262-63111-3. (First edition, Massachusetts Institute of Technology, 1969).
Minton, S. (1984). Constraint Based Generalization: Learning Game Playing Plans from Single Examples. Proceedings of the 4th National Conference on Artificial Intelligence (AAAI-84), pp. 251 254. Morgan Kaufmann, Los Altos, CA.
Minton, S. (1985). A Game-Playing Program that Learns by Analyzing Examples. Report CMU-CS-85-130. Carnegie-Mellon University, Boston, Massachusets.
Minton, S., Carbonell, J., Knoblock, C., Kuokka, D., Etzioni, O., and Gil, Y. (1989). Explanation Based Learning: A Problem-Solving Perspective. Artificial Intelligence, Vol. 40, Nos. 1-3, pp. 63-118. ISSN 0004-3702.
Mitchell, T.M. (1997). Machine Learning. WCB McGraw-Hill, pp. 92-94. ISBN 0-07-042807-7.
Minton, S. (1990). Quantitative Results Concerning the Utility of Explanation Based Learning. Artificial Intelligence, Vol. 42, pp. 363 392. ISSN 0004-3702.
Mitchell, T.M., Keller, R.M., and Kedar Cabelli, S. (1986). Explanation Based Generalization: A Unifying View. Machine Learning, Vol. 1, No. 1, pp. 47 80. ISSN 0885-6125.
Monien, B. and Vornberger, O. (1987). Parallel Processing of Combinatorial Search Trees. International Workshop on Parallel Algorithms and Architectures 1987, Math. Research Nr. 38, pp. 60-69, Akademie-Verlag, Berlin, Germany.
Moore, D.S. and McCabe, G.P. (1993). Introduction to the Practice of Statistics. W.H. Freyman, 2nd edition. ISBN 0-716-72250-X.
Moore, J.D. and Swartout, W.R. (1988). Explanation in Expert Systems: A Survey. ISI Research Report RR 88 228, University of Southern California.
Morales, E. (1991). Learning Features by Experimentation in Chess. Proceedings of the 5th European Working Session on Learning (EWSL-91) (ed. Y. Kodratoff), pp. 494 511. Springer-Verlag, Berlin. ISBN 3-540-53816-X.
Morales, E. (1992). First Order Induction of Patterns in Chess. Ph.D. Thesis, The Turing Institute - University of Strathclyde.
Morales, E. (1992). Learning Chess Patterns. Inductive Logic Programming (ed. S. Muggleton), pp. 517-537. Academic Press, The Apic Series, London, UK. ISBN 0-12-509715-8.
Morales, E. (1994). Learning Patterns for Playing Strategies. ICCA Journal, Vol. 17, No. 1, pp. 15-26. ISSN 0920-234X.
Morales, E. and Morales-Manzanares, R. (1995). Learning Musical Rules. Proceedings of the IJCAI-96 Workshop: Artificial Intelligence and Music (ed. G. Widmer), pp. 81-85. Montreal, Canada.
Morales, E. (1996). Learning Playing Strategies in Chess. Computational Intelligence, Vol. 12, No. 1, pp. 65-87. ISSN 0824-7935.
Morales, E.F. (1997). On Learning How to Play. Advances in Computer Chess 8 (eds. H.J. van den Herik and J.W.H.M. Uiterwijk), pp. 235-250. Universiteit Maastricht, Maastricht, The Netherlands. ISBN 90-6216-2347.
Moreland, b. (2002)., Computer Chess. http://www.seanet.com/~brucemo/chess.htm.
Moriarty, D.E. and Miikkulainen, R. (1994). Evolving neural networks to focus minimax search. Proceedings of the 13th National Conference on Artificial Intelligence (AAAI-94), pp. 1371-1377. AAAI Press, Menlo Park, CA.
Moriarty, D.E. and Miikkulainen, R. (1996). Efficient Reinformcement Learning through Symbiotic Evolution. Machine Learning, Vol 22, Nos. 1-3, pp. 11-32.
Morse, J. (1995). Chess Problems: Tasks and Records. Faber and Faber, London. ISBN 0-5711-5363-1.
Moser, L. (1984). An Experiment in Distributed Game Tree Searching, University of Waterloo.
Mozetic, I., Bratko, I. and Lavrac, N. (1987). Automatic synthesis and compression of electrocardiological knowledge. Machine Intelligence 11 (eds. J. Hayes, D. Michie and J. Richards), Oxford University Press (to appear).
MPI (2002). MPICH – A Portable Implementation of MPI. http://www-unix.mcs.anl.gov/mpi/impich/.
MPI (2004a). Message Passing Interface (MPI) Forum Home Page. http://www.mpi-forum.org/.
MPI (2004b). Mpich2 Home Page. http://www-unix.mcs.anl.gov/mpi/mpich2/index.htm.
Muggleton, S.H. (1987). Duce, an oracle-based approach to constructive induction. Proceedings of the 10th IJCAI Conference, Milano, Italy (to appear).
Muggleton, S.H. (1988). Inductive Acquisition of Chess Strategies. Machine Intelligence 11 (eds. J.E. Hayes, D. Michie, and J. Richards), pp. 375-389. Clarendon Press, Oxford, U.K. ISBN 0-19-853718-2.
Muggleton, S. (1990). Inductive Acquisition of Expert Knowledge. Turing Institute Press. Addison Wesley Reading, MA. ISBN 0-201-17561-4.
Muggleton, S. and Feng, C. (1990). Efficient Induction of Logic Programs. Proceedings of the First International Workshop on Algorithmic Learning Theory (ALT90) (eds. S. Arikaxa, S. Soto, S. Ohsuya, and T. Yokomari), pp. 368-381. Ohmsha, Tokyo, Japan.
Muggleton, S. (1991). Inductive Logic Programming. New Generation Computing, Vol. 8, pp. 295-318. ISSN 0228-3635.
Muggleton, S. (ed.) (1992). Inductive Logic Programming. Academic Press Ltd., London, UK. ISBN 0-12-509715-8.
Müller, K. (2003). Man Equals Machine in Chess. ICGA Journal, Vol. 26, No. 1, pp. 9-13.
Müller, K. and Lamprecht, F. (1999). Secrets of Pawn Endings. Everyman. ISBN 1-8574-4255-5.
Müller, K. and Lamprecht, F. (2001). Fundamental Chess Endings. Gambit. ISBN 1-9019-8353-6.
Müller, K. (2002). The Clash of the Titans: Kramnik – Fritz Bahrain. ICGA Journal, Vol. 24, No. 4, pp. 233-239.
Muller, M. (1991). The Smart Game Board as a Tool for Game Programmers. Heuristic Programming in Artificial Intelligence 2: the second computer olympiad (eds. D.N.L. Levy and D.F. Beal), pp. 217-231. Ellis Horwood Ltd., Chichester, UK. ISBN 0-13-382615-5.
Müller, M. (1995). Computer Go as a Sum of Local Games: An Application of Combinatorial Game Theory. Ph.D. Thesis. ETH Zürich, Switzerland.
Müller, M. (1996). Computer Go as a Sum of Local Games: An Application of Combinatorial Game Theory. Ph.D. Thesis, ETH Zürich, 1995. Diss. ETH Nr. 11.006.
Müller, M. and Gasser, R. (1996). Experiments in Computer Go Endgames. Games of No Chance: Combinatorial Games at MSRI (ed. R.J. Nowakowski), pp. 273-284. Cambridge University Press, Cambridge, MA.
Müller, M., Berlekamp, E., and Spight, B. (1996). Generalized Thermography: Algorithms, Implementation, and Appliation to Go Endgames. ICSI Technical Report 96-030. International Computer Science Institute, Berkeley.
Müller, M. (1997). Playing it Safe: Recognizing Secure Territories in Computer Go by Using Static Rules and Search. Game Programming Workshop in Ja­pan ’97 (ed. H. Matsubara), pp. 80-86. Computer Shogi Association, Tokyo, Japan.
Müller, M. (1998). Computer Go: A Research Agenda. Computers and Games (eds. H.J. van den Herik and H. Iida), pp. 252-264. Lecture Notes in Computer Sciencee, No.1558, pp. 252-264. Springer-Verlag, Heidelberg, Germany. ISBN 3-540-65766-5.
Müller, M. (1999a). Decomposition Search: A Combinatorial Games Approach to Game Tree Search, with Applications to Solving Go Endgames, IJCAI-99, pp. 578-583. Morgan Kaufmann, San Mateo, CA. ISBN 1045-0823.
Müller, M. (1999b). Race to Capture: Analyzing Semeai in Go. Game Programming Workshop in Japan ’99 (ed. H. Matsubara). IPSJ Symposium Series. Vol. 99, No. 14, pp. 61-68.
Müller, M. and Lamprecht, F. (1999). Secrets of Pawn Endings. Everyman. ISBN 1-8574-5255-5.
Müller, M. (2000). Generalized Thermography: A New Approach to Evaluation in Computer Go. Games in AI Research (eds. H.J. van den Herik and H. Iida), pp. 203-219. Universiteit Maastricht, Maastricht, The Netherlands. ISBN 90-621-6416-1.
Müller, M. (2001). Partial order bounding: A new approach to evaluate in game tree search, Artificial Intelligence, Vol. 129, Nos. 1-2, pp. 279-311. ISSN 0004-3702.
Müller, M. (2001). Global and local game tree search. Information Sciences, 135(3-4):187-206. ISSN 0020-0255.
Müller, M. and Lamprecht, F. (2001). Fundamental Chess Endings. Gambit. ISBN 1-9019-8353-6.
Müller, M. (2002a). Computer Go. Artificial Intelligence, Vol. 134, Nos. 1-2, pp. 145-179. ISSN 0004-3702.
Müller, M. (2002b). Position Evaluation in Computer Go. ICGA Journal, Vol. 25, No. 4, p. 219-228.
Müller, T., Popov, K., Schulte, Chr., and Würtz, J. (1994). Constraint Programming in Oz. DFKI Oz documentation series, Saarbrücken, Germany.
Murray, H.J.R. (1913). A History of Chess. Oxford University Press, Oxford.
Murray, H. J.R. (1952). A History of Board Games other than Chess. Oxford at the Clarendon Press, London, UK. ISBN 0-87817-211-4.
Muszycka, A. and Shinghal, R. (1985). An Empirical Comparison of Pruning Strategies in Game Trees. IEEE Transactions, Vol. SMC 15, No. 3, pp. 389 399.
Myers, B. (2002). The 21st Century Championship Cup 2002. ICGA Journal, Vol. 25, No. 4, p. 245.
Mysliwietz, P. (1994). Konstruktion und Optimierung von Bewertungs-funktionen beim Schach. Ph.D. Thesis. University of Paderborn, Paderborn, Germany.
Mysliwietz, P.(1997). A Metric for Evaluation Functions. Advances in Computer Chess 8 (eds. H.J. van den Herik and J.W.H.M. Uiterwijk), pp. 181-198. Universiteit Maastricht, Maastricht, The Netherlands. ISBN 90-6216-2347.
0 (1971). Computer Recreations. Software - Practice and Experience, Vol. 1, No. 2, pp. 201-204. ISSN 0038-0644.
Nagai, A. (1998). A new AND/OR Tree Search Algorithm Using Proof Number and Disproof Number. Proceedings of Complex Games Lab Workshop, pp. 40-45, ETL, Tsukuba, Japan.
Nagai, A. (1999). A New Depth-First-Search Algorithm for AND/OR Trees. M.Sc. Thesis, Department of Information Science, The University of Tokyo, Japan.
Nagai, A. (1999). Proof for the Equivalence Between Some Best-First Algorithms and Depth-First Algorithms for AND/OR Trees. KOREA-JAPAN Joint Workshop on Algorithms and Computation, pp. 163-170.
Nagai, A. and Imai, H. (1999). Application of df-pn+ to {Othello} Endgames. Proceedings of Game Programming Workshop in Japan '99, pp. 16-23, Hakone, Japan.
Nagai, A. (2000). The Recent Achievement of Computer Tsume-Shogi: Challenges in Solving Problems with Extremely Long Steps. Journal of Computer Shogi Association, Vol. 13, pp. 34-42. (in Japanese).
Nagai, A. (2002). Df-pn Algorithm for Searching AND/OR Trees and Its Application, Ph.D. thesis, Department of Information Science, University of Tokyo.
Nagi, W. (1989). Best-Move-Proving: A Fast Game-Tree Searching Algorithm. Heuristic Programming in Artificial Intelligence: the first computer olympiad (eds. D.N.L. Levy and D.F. Beal), pp. 255-272. Ellis Horwood, Chichester. ISBN 0-7458-0778-X.
Nakamura, K. (2000). Graph Theoretic Analyses of Go Board Phases. Games in AI Research (eds. H.J. van den Herik and H. Iida), pp. 239-249. Universiteit Maastricht, Maastricht, The Netherlands. ISBN 90-621-6416-1.
Nakamura, K. (2001). Analyzing Capturing Races and Seki Situations. Advances in Computer Games 9 (eds. H.J. van den Herik and B. Monien), pp. 295-311. IKAT, Universiteit Maastricht, Maastricht, The Netherlands. ISBN 90-6216-5761 / 90-6216-5664.
Nakamura, K. and Kitoma S. (2002). Analyzing Go Board Patterns Based on Numerical Features. Journal of IPSJ, vol. 43, No. 10, pp. 3021-3029 (in Japanese).
Nakaie, H., Iida, H., and Kotani, Y. (1996). A Method of Applying Opening Book Data to Non-Recorded Positions. Game Programming Workshop ’96, (ed. H. Matsubara), pp. 218-227.
Nakaie, H. and Kotani, Y. (1997). A Method of Applying Opening Book Data by Partial Matching. Game Programming Wokshop ’97, (ed. H. Matsubara), pp. 106-113.


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