These bibliographies were put together by Anders Kierulf, Peter Lipp, Martin Muller and others.
Allis/v.d.Herik/Herschberg 91 Which games will survive? ALLIS, L.V., VAN DEN HERIK, H.J., HERSCHBERG, I.S. In: [Levy/Beal 91].
Benson 80 A mathematical analysis of Go. BENSON, D.B. In: Proc. of the 2nd Seminar on Scientific Go-Theory. HEINE, K. (ed.) Institut für Strahlenchemie, Mühlheim a. d. Ruhr (1979), pp.55-64.
Benson, D. B., Hilditch, B. R., and Starkey, J. D. Tree-analysis techniques in Tsumego.In Proceedings of the International Joint Conference on Artificial Intelligence, pages 50 - 52, 1979.
Benson, D. B.. Life in the game of go. Information Sciences, 10:17 - 29, 1976.
Berlekamp 91 Introductory Overview of Mathematical Go Endgames. BERLEKAMP, E. In: Proc. of Symposia in Applied Mathematics, Vol. 43, Combinatorial Games, pp. 73-100.
Berlekamp 92 Mathematical Go: Thermographs find the biggest move asymptotically. BERLEKAMP, E. Unpublished manuscript, 1992.
Berlekamp/Conway/Guy 82 Winning Ways. BERLEKAMP, E., CONWAY, J.H., GUY, R.K. Academic Press, London 1982.
Berlekamp/Kim 94 Where is the "$1,000 Ko"?. BERLEKAMP, E., KIM, Y. Go World No. 71, pp. 65-80, Ishi Press 1994.
Berlekamp/Wolfe 94 Mathematical Go: Chilling Gets the Last Point. BERLEKAMP, E., WOLFE, D. A K Peters, Wellesley 1994.
Boon 90 A Pattern Matcher for Goliath. BOON, M., Computer Go 13, p.12-23.
Bozulich 92 The Go Player's Almanac, BOZULICH, R. (Ed.), Ishi Press, Tokyo 1992
Brügmann 93 Monte Carlo Go. BRüGMANN, B., Report available by ftp from bsdserver.ucsf.edu.
Bramer 83 Computer Game-Playing: Theory and Practice. BRAMER, M.A. (Ed.) Ellis Horwood Ltd., Chichester, West Sussex, 1983.
Brown, D. J. H. Hierarchical reasoning in the game of Go. In Proceedings of the 6th International Joint Conference on Artificial Intelligence, pages 114 -116, 1979.
Chen 89 Group Identification in Computer Go. CHEN, K. [Levy/Beal 89], 195-210.
Chen 93 Binary Game Forest - An approximation model for Go. CHEN, K., unpublished report, 1993.
Chen, K. Group identification in computer Go. In D. N. L. Levy and D. Beal, editors, Heuristic Programming in Artificial Intelligence: the First Computer Olympiad, pages 195 - 210. Ellis Horwood, Chichester, 1989.
Chen/Kierulf/Müller/Nievergelt 90 The Evolution of Go Explorer. CHEN, K.; KIERULF, A.; MüLLER, M.; NIEVERGELT, J. In: Computers, Chess, and Cognition, MARSLAND, T. A.; SCHAEFFER, J. (Eds.), Springer Verlag, 1990.
Conway 76 On Numbers and Games. CONWAY, J., Academic Press, London/New York 1976.
Donnelly, P., Corr, P., and Crookes, D. Evolving Go playing strategy in neural networks. Anonymous ftp from swan.cl.cam.ac.uk- reports/TR275-bdp-go.ps.gz.
Dudey, P. The long road ahead: Difficulties in machine intelligence. Anonymous ftp from bsdserver.ucsf.edu - Go/comp/longroad.Z, 1992.
Eisenstadt, M., and Kareev, Y. Aspects of human problem solving: The use of internal representations. In D. A. Norman and D. E. Rumelhart, editors, Explorations in Cognition, pages 308 - 346. W. H. Freeman, San Francisco, 1975.
Enderton 91 The Golem Go Program. ENDERTON, H.D., Technical report CMU-CS-92-101, Carnegie Mellon University, 1991. Report available by ftp from bsdserver.ucsf.edu.
Erbach 92 Computers and Go. ERBACH, D.W. In: [Bozulich 92].
Fierz 92 Go Endgames. FIERZ, W., Semesterarbeit, ETH Zürich 1992.
Fotland 93 Knowledge Representation in The Many Faces of Go. FOTLAND, D. Report posted on internet newsgroup rec.games.go, 1993. Available by ftp from bsdserver.ucsf.edu.
Fotland 94 Many Faces of Go. FOTLAND, D., World-Wide-Web page, 1994. Location: http://cgl.ucsf.edu/go/Programs/ManyFaces.html.
Fotland, D. Knowledge representation in the many faces of Go. Anonymous ftp from bsdserver.ucsf.edu - Go/comp/article.Z.
Friedenbach 80 Abstraction Hierarchies: A Model of Perception and Cognition in the Game of Go. FRIEDENBACH, K. J. Ph.D. Thesis, Univ. of California, Santa Cruz, 1980.
Friedenbach, K. J. Abstrction Hierarchies: A Model of Perception and Cognition in the Game of Go. PhD., University of California, Santa Cruz., 1980.
Gasser 90 Heuristic Search and Retrograde Analysis: their Application to Nine Men's Morris. GASSER, R., Diploma thesis, ETH Zürich 1990.
Gasser 91 Applying Retrograde Analysis to Nine Men's Morris. GASSER, R. In: Gasser 92 GASSER, R., personal communication.
Gasser 94 Efficiently Harnessing Computational Resources for Exhaustive Search. GASSER, R., Dissertation, ETH Zürich, 1994.
Geiser 91 Pattern Recognition in the Game of Go. GEISER, P.M., Diploma thesis, ETH Zürich 1991.
Gonnet 88 Efficient Searching of Text and Pictures. GONNET, G.H., Extended Abstract, UW Center for the New Oxford English Dictionary, June 1988
High 92 Mathematical Go. HIGH, R.G. In: [Bozulich 92], p.218-224.
Kageyama 78 Lessons in the Fundamentals of Go. KAGEYAMA, T., Ishi Press, Tokyo 1978.
Kano 85 Graded Go Problems for Beginners. KANO, Y., Nihon Ki-in, Tokyo 1985.
Kierulf 82 Brand - an Othello Program. KIERULF, A. In: [Bramer 83]
Kierulf 89a Peer Gynt vs. Bill. KIERULF, A. Othello Quarterly 11, 2 (Summer 1989), 6-8.
Kierulf 89b Quo Vadis Go Explorer. KIERULF, A. unpublished manuscript, ETH Zürich, 1989.
Kierulf 90 Smart Game Board: a Workbench for Game-Playing Programs, with Go and Othello as Case Studies. KIERULF, A. Dissertation, ETH Zürich, 1990.
Kierulf, A. Human-computer interaction in the game of Go. Methodologies for Intelligent Systems, 1987.
Kierulf, A., Chen, K., and Nievergelt, J. Smart game board and Go Explorer: a study in software and knowledge engineering. Communications of the ACM, 33(2):152 - 167, February 1990.
Kierulf/Chen/Nievergelt 90 Smart Game Board and Go Explorer: A case study in software and knowledge engineering. KIERULF, A.; CHEN, K.; NIEVERGELT, J. Comm. ACM, February 1990.
Kierulf/Gasser/Geiser/Müller/Nievergelt/Wirth 91 Every interactive system evolves into hyperspace: The case of the Smart Game Board. KIERULF, A.; GASSER, R.; GEISER, P.; MüLLER, M.; NIEVERGELT, J. In: Proc. Hypertext/Hypermedia 1991, MAURER, H. (Ed.), Springer.
Kierulf/Nievergelt 85 Computer Go: A Smart Go Board and its Applications. KIERULF, A.; NIEVERGELT, J., In: Go World No.42, pp62-64, Winter 1985/86.
Kierulf/Nievergelt 89 Swiss Explorer blunders its way into winning the first Computer Go Olympiad. KIERULF, A.; NIEVERGELT, J. In [Levy/Beal 89], 51-55.
Kok, Z., and Akman, V. Field: A data type for automated perception in Go. Computer and Information Sciences VI, pages 641 - 650, 1991. 2
Kopec/Bratko 82 The Bratko-Kopec Experiment: A Comparison of Human and Computer Performance in Chess. KOPEC, D., and BRATKO, I. [Clarke 82]
Kraszek 88 Heuristics in the Life and Death Algorithm of a Go-playing Program. KRASZEK, J., In: Computer Go 9, p.13, 1988.
Lehner, P. E. Planning in Adversity: A Computational Model of Strategic Planning in the Game of Go. PhD., Department of Psychology, The University of Michigan., 1981.
Lenz 82 Die Semeai-Formel. LENZ, K.F. Deutsche Go-Zeitung 57, No.4, 1982.
Levy 88 Computer Games I+II. LEVY, D.N.L. (Editor), Springer, 1988.
Levy/Beal 89 Heuristic Programming in Artificial Intelligence - The First Computer Olympiad. LEVY, D.N.L.; BEAL, D.F. (Eds.) Ellis Horwood Ltd., Chichester, West Sussex, 1989.
Levy/Beal 91 Heuristic Programming in Artificial Intelligence 2. LEVY, D.N.L., and BEAL, D.F.(eds.), Ellis Horwood 1991.
Lichtenstein, D., and Sisper, M. Go is polynomial-space hard. Journal of the ACM, 27(2):393 - 401, April 1980.
Müller 89 Eine Theoretische Basis zur Programmierung von Go. MüLLER, M. Diploma thesis, Techn. University of Graz, Austria, April 1989.
Müller 90 The Smart Game Board as a Tool for Game Programmers. MüLLER, M. In: Heuristic Programming in Artificial Intelligence 2, LEVY, D.N.L.; BEAL, D.F. (Eds.), London 1990
Müller 91a Measuring the performance of Go programs. MüLLER, M. In: Proc. International Go Congress, Beijing 1991.
Müller 91b Pattern Matching in Explorer. MüLLER, M. In: Proc. of the Game Playing System Workshop, ICOT, Tokyo 1991.
Müller 93 Game Theories and Computer Go. MüLLER, M. In: Proc. of the Go and Computer Science Workshop (GCSW'93), INRIA, Sophia-Antipolis, 1993
Müller 94 Explorer User Manual. MüLLER, M. Internal report, ETH Zürich 1994.
Müller/Gasser 94 Experiments in Computer Go Endgames. MüLLER, M., and GASSER, R. To appear in: Proceedings of MSRI Workshop on Combinatorial Games.
Mano, Y. An approach to conquering difficulties in developing a Go-playing program. Journal of Information Processing, 7:81 - 88, 1984.
Marsland/Schaeffer 90 Computers, Chess, and Cognition. MARSLAND, T. A.; SCHAEFFER, J. (Eds.), Springer Verlag, 1990.
Marzetta 92 MARZETTA, A. Personal Communication, 1992.
Millen, J. K. Programming the game of Go. BYTE, 6(4):102 - 120, April 1981.
Miller 76 The End Game of Go. MILLER, J. In: Proc. Northwest 76 ACM/CIPS Pacific Regional Symposium (Seattle Pacific College, Seattle, Washington, June 24-25, 1976).
Moews 93 On Some Combinatorial Games Connected with Go. MOEWS, D.J., Dissertation, University of California at Berkeley, 1993.
Pell, B. Exploratory learning in the game of Go. In D. N. L. Levy and D. F. Beal, editors, Heuristic Programming in Artificial Intelligence 2 - The second Computer Olympiad, volume 2. Ellis Horwood, 1991.
Peter 93 Erweitertes Pattern Matching in Go. PETER, H.E., Diploma thesis, ETH Zürich.
Pettersen 94 The Computer Go Ladder. PETTERSEN, E., World Wide Web page, http://cgl.ucsf.edu/go/ladder.html, 1994.
Popma/Allis 92 Life and Death refined. POPMA, R.; ALLIS, L.V. In: Heuristic Programming in Artificial Intelligence 3, VAN DEN HERIK, J., and ALLIS, L.V. (Eds.), Ellis Horwood 1992, p.157-164.
Reitman, J. S. Skilled perception in Go: Deducing memory structures from inter-response times. Cognitive Psychology,8, pages 336 - 356, 1976.
Reitman, W., and Wilcox, B. Modelling tactical analysis and problem solving in Go. In Proceedings of the Tenth Annual Pittsburg Conference on Modelling and Simulation, pages 2133 - 2148, Pittsburg, 1979. Instrument Society of America.
Reitman, W., and Wilcox, B. Pattern Recognition and Pattern-directed Inference in a Program for Playing Go. In D. Waterman and F. Hayes-Roth, editors, Pattern Directed Inference Systems, pages 503 - 523. Academic Press, New York, 1978.
Reitman, W., and Wilcox, B. Perception and representation of spatial relation in a program for playing Go. In Proceedings of the 30th National Conference of the ACM, pages 37 - 41. ACM, 1975.
Reitman, W., and Wilcox, B. The structure and performance of the Interim.2 Go program. In Proceedings of the Joint Conference on Artificial Intelligence, pages 711 - 719, 1979.
Reitman, W., Kerwin, J., Nado, R., Reitman, J., and Wilcox, B. Goals and plans in a program for playing Go. In Proceedings of the 29th National Conference of the ACM, pages 123 - 127, San Diego, 1974. ACM.
Remus, H. Simulation of a learning machine for playing Go. In Proceedings of the International Federeation of Information Processing Congress, pages 428 - 432, Amsterdam, 1962. International Federation of Information Processing Congress, North- Holland Publishing Company.
Robson 83 The Complexity of Go. ROBSON, J.M. Proc. IFIP (International Federation of Information Processing), (1983), 13-417.
Robson, J. M. The complexity of Go. In R. E. A. Mason, editor, Proceedings of the IFIP 9th World Computer Congress, pages 413 - 417, North-Holland, September 1983. IFIP, Elsevier Science Publishers.
Ryder 71 Heuristic Analysis of Large Trees as Generated in the Game of Go. RYDER, J. L. Stanford Univ., Ph.D. Thesis, (1971), 1-298 (Microfilm 72-11, 654).
Ryder, J. L. Heuristic Analysis of Large Trees as generated in the Game of Go. PhD thesis, Department of Computer Science, Standford University., August 1971.
Sander, P. T., and Davies, D. J. M. A strategic approach to the game of Go. In M. A. Bramer, editor, Computer Game-Playing: Theory and Practice. Ellis Horwood, Chichester, 1983.
Schraudolph 94 Temporal Difference Learning of Position Evaluation in the Game of Go. SCHRAUDOLPH , N. In: Neural Information Processing Systems 6, Morgan Kaufmann 1994. Also available by ftp from bsdserver.ucsf.edu.
Sedgewick 83 Algorithms. SEDGEWICK, R. Addison-Wesley, 1983.
Stoutamire 91 Machine Learning, Game Play, and Go. STOUTAMIRE, D., Reprint of Master's thesis, available by ftp from bsdserver.ucsf.edu, 1991.
Stoutamire, D. Machine learning, game play and Go. Technical Report TR 91-128, Case Western Reserve University, Cleveland, Ohio., 1991.
Takagawa 85 How Many Moves is it Possible to Read? TAKAGAWA, S. Go World No.41, pp.30-33, Autumn 1985.
Thorp, E. O. and Walden, W. E. A computer-assisted study of Go on m x n boards. Information Sciences, 4:1 - 33, 1972.
Thorp, E. O., and Walden, E. W. A partial analysis of Go. The Computer Journal, 7(3):203 - 207, 1964.
Thorp/Walden 64 A Partial Analysis of Go. THORP, E.; WALDEN, W.E. Computer Journal, Vol.7, No.3, pp. 203-207, 1964. Reprinted in: [Levy 88], Vol.II, pp.143-151.
Thorp/Walden 72 A Computer Assisted Study of Go on M*N Boards. THORP, E.; WALDEN, W.E. Inf. Sciences, Vol.4 No.1, pp.1-33, 1972. Reprinted in: [Levy 88], Vol.II, pp.152-181.
Turing et al. 53 Digital Computers applied to Games. TURING, A.M., STRACHEY, C., BATES, M.A., BOWDEN, B.V. In: Faster than thought, BOWDEN, B.V. (Ed.), Pitman, London 1953, p. 286-297.
Wilcox 79 Computer Go - The Reitman-Wilcox Program. WILCOX, B. American Go Journal 14, 5/6 (1979), 23-41.
Wilcox, B. Computer Go. In D. N. L. Levy, editor, Computer Games, volume 2, pages 94 - 135. Springer-Verlag, New York, 1988.
Wilcox, B. Reflections on building two Go programs. ACM SIGART Newsletter, pages 29 - 43, October 1985.
Wolf 91 Investigating Tsumego Problems with RisiKo. WOLF, T., In: [Levy/Beal 91].
Wolfe 91 Mathematics of Go: Chilling Corridors. WOLFE, D., Dissertation, Univ. of California, Berkeley 1991.
Wolfe91 WOLFE, D., Games program available via anonymous ftp from milton.u.washington.edu (128.95.136.1), file theory.sh.Z.
Zobrist 70a Feature Extraction and Representation for Pattern Recognition and the Game of Go. ZOBRIST, A. L. Ph.D. Thesis, Univ. of Wisconsin, 1970, 1-152. (Microfilm 71-03, 162).
Zobrist, A. L. A model of visual organisation for the game Go. In Proceedings of the Spring Joint Computer Conference, volume 34, pages 103 - 112, 1969.