being one of the first hints. With the invention of computers, this idea got a new boost, and soon the first chess programs were presented. It took about 50 years until it was clear that the machines are superior chess players, far beyond the playing strengths of any human players. In the 1970s, the era of efficient search engines started and in 2004, the chess program Hydra clearly crossed the 3000 Elo mark, ahead of all other machines and human players. In this paper, we present a review on the chess program Hydra, on a technical level as well as from a social perspective.
Ali, M.N. & Friedel, F. (2003). All about the Hydra chess project. Chess News. https://en.chessbase.com/post/all-about-the-hydra-che-project.
2.
Althöfer, I. (1988). Root evaluation errors: How they arise and propagate. ICCA Journal, 11(3), 55–63.
3.
Berliner, H.J. (1985). HiTech wins North American Computer-Chess Championship. ICCA Journal, 8(4).
4.
Bernstein, A., Arbuckle, T., De Roberts, M.V. & Belsky, M. (1958). A chess playing program for the IBM 704. In Proceedings of the May 6–8, 1958, Western Joint Computer Conference: Contrasts in Computers (pp. 157–159).
5.
Björnsson, Y. & Marsland, T. (2001). Multi-cut alphabeta-pruning in game tree search. Theoretical Computer Science, 252, 177–196. doi:10.1016/S0304-3975(00)00081-5.
6.
Buro, M. (1999). Toward opening book learning. ICGA Journal, 22(2), 98–102. doi:10.3233/ICG-1999-22204.
7.
Campbell, M. (1999). Knowledge discovery in Deep Blue. Communications of the ACM, 42(11), 65–67. doi:10.1145/319382.319396.
8.
Campbell, M., Hoane, A.J.Jr. & Hsu, F.-h. (2002). Deep blue. Artificial Intelligence, 134(1–2), 57–83. doi:10.1016/S0004-3702(01)00129-1.
9.
Condon, J.H. & Thompson, K. (1982) M.R.B.Clarke (Ed.), Belle Chess Hardware. Advances in Computer Chess III (pp. 44–54). Pergamon Press.
10.
de Groot, A.D. (2008). Thought and Choice in Chess. Amsterdam University Press. http://www.jstor.org/stable/j.ctt46n0r2.
11.
Donninger, C. (1993). Null move and deep search. ICCA Journal, 16(3), 137–143.
12.
Donninger, C. & Lorenz, U. (2004). The chess monster hydra. In Proc. of International Conference on Field-Programmable Logic and Applications (FPL). LNCS (Vol. 3203, pp. 927–932). Antwerp - Belgium. doi:10.1007/978-3-540-30117-2_101.
13.
Donninger, C. & Lorenz, U. (2006). Innovative opening-book handling. In H.J.van den Herik, S.-C.Hsu, T.-s.Hsu and H.H.L.M.J.Donkers (Eds.), Advances in Computer Games (pp. 1–10). Berlin Heidelberg: Springer.
14.
Dubey, R. (2008). Introduction to Embedded System Design Using Field Programmable Gate Arrays (1st ed.). Springer.
15.
Feldmann, R. (1993). Game Tree Search on Massively Parallel Systems. PhD thesis, University of Paderborn.
16.
Feldmann, R., Monien, B., Mysliwietz, P. & Vornberger, O. (1990). Distributed game tree search. In V.Kumar, P.S.Gopalakrishnan and L.N.Kanal (Eds.), Parallel Algorithms for Machine Intelligence and Vision (pp. 66–101). Springer. doi:10.1007/978-1-4612-3390-9_3.
17.
Ferguson, C. & Korf, R.E. (1988). Distributed tree search and its application toalpha-beta pruning. In Proceedings of the Seventh National Conference Artificial Intelligence (AAAI-88), Minneapolis, MN (pp. 128–132).
18.
Hallworth, E. (2005). In E.Hallworth (Ed.), Mickey Adams v Hydra. Selective Search 120 – the Computer Chess Magazine (Vol. 120, pp. 6–13). http://www.chesscomputeruk.com/SS_120.pdf.
19.
Hsu, F,-h., Anantharaman, T.S., Campbell, M.S. & Nowatzyk, A. (1990). Deep thought. In Computers, Chess, and Cognition (pp. 55–78). Springer. doi:10.1007/978-1-4613-9080-0_5.
20.
Hyatt, R.M., Gower, B.E. & Nelson, H.L. (1985). Cray blitz. In D.F.Beal (Ed.), Advances in Computer Chess IV (pp. 8–18). Pergamon Press.
21.
Knuth, D.E. & Moore, R.W. (1975). An analysis of alpha-beta pruning. Artificial Intelligence, 6(4), 293–326. doi:10.1016/0004-3702(75)90019-3.
22.
Lorenz, U. (2004). Beyond optimal play in two-person-zerosum games. In Proc. of Annual European Symposium on Algorithms, ESA’04 (pp. 749–759).
23.
Lorenz, U. & Monien, B. (2002). The secret of selective game tree search, when using random-error evaluations. In H.Alt and A.Ferreira (Eds.), Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science (STACS). LNCS (pp. 203–214). Springer.
24.
Lorenz, U. & Monien, B. (2004). In Error Analysis in Minimax Trees. Theoretical Computer Science (Vol. 313, pp. 485–498).
25.
Marsland, T.A., Olafsson, M. & Schaeffer, J. (1986). Multiprocessor tree-search experiments. In D.F.Beal (Ed.), Advances in Computer Chess (Vol. 4, pp. 37–51). Pergamon Press.
26.
Pearl, J. (1983). On the nature of pathology in game searching. Artificial Intelligence, 20(4), 427–453. doi:10.1016/0004-3702(83)90004-8.
27.
Reinefeld, A. (1983). An improvement to the scout tree-search algorithm. ICCA Journal, 6(6), 4–14.
28.
Scheucher, A. & Kaindl, H. (1989). The reason for the benefits of minimax search. In Proceedings of the 11th International Joint Conference on Artificial Intelligence – Volume 1. IJCAI’89 (pp. 322–327). San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.
29.
Schrüfer, G. (1986). Presence and absence of pathology on game trees. In D.F.Beal (Ed.), Advances in Computer Chess (Vol. 4, pp. 101–112). Pergamon Press.
30.
Slate, D.J. & Atkin, L.R. (1977) P.W.Frey (Ed.), CHESS 4.5 – the Northwestern University Chess Program. Chess Skill in Man and Machine (pp. 82–118). Springer.
31.
van den Herik, H. (2004). The world chess team championship man vs. machine. ICGA Journal, 27(4), 246–248. doi:10.3233/ICG-2004-27413.
32.
ChessBase, van den Herik, H.J., Nunn, J. & Levy, D. (2005). Adams outclassed by Hydra. ICGA Journal, 28(2), 107–110. https://pure.uvt.nl/ws/portalfiles/portal/1258781/INFORMA6.PDF. doi:10.3233/ICG-2005-28206.
