Abstract
Recently computers have gained strength in the Asian board game Go. The Chess community experienced some 15 to 30 years ago that teams with humans and computers may be much stronger than each of their components. This paper claims that time is ripe for computer-aided Go on a large scale, although neither most users nor the Go programmers have realized it. A central part of the paper describes successful pioneers in Go play with computer help. Progress in computer-aided Go may also lead to progress in human Go and in computer Go itself.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Althöfer, I., Donninger, C., Lorenz, U., Rottmann, V.: On timing, permanent brain and human intervention. In: Van den Herik, H., Herschberg, I.S., Uiterwijk, J., (ed.) Advances in Computer Chess 7, pp. 285–296. University of Limburg Press (1994)
Althöfer, I., Kaitschick, S., Marz, M.: Computer-aided go on high-dan level. In: IGGSC Proceedings, Charles University, Prague (2015)
Althöfer, I., de Koning, J., Lieberum, J., Meyer-Kahlen, S., Rolle, T., Sameith, J.: Five visualisations of the k-best mode. ICGA J. 26, 182–189 (2003)
Althöfer, I.: 13 Jahre 3-Hirn: Meine Schach-Experimente mit Mensch-Maschinen-Kombinationen. 3-Hirn-Verlag (1998)
Althöfer, I.: Improved game play by multiple computer hints. Theor. Comput. Sci. 313(3), 315–324 (2004)
Althöfer, I., Snatzke, R.G.: Playing games with multiple choice systems. In: Schaeffer, J., Müller, M., Björnsson, Y. (eds.) CG 2002. LNCS, vol. 2883, pp. 142–153. Springer, Heidelberg (2003). doi:10.1007/978-3-540-40031-8_10
Cook, D.: A human-computer team experiment for 9x9 go. In: Herik, H.J., Iida, H., Plaat, A. (eds.) CG 2010. LNCS, vol. 6515, pp. 145–155. Springer, Heidelberg (2011). doi:10.1007/978-3-642-17928-0_14
Metz, H., Wüllenweber, M.: Interview on the history and current role of the chessbase company in the chess world. Schach-Magazin 64, January 2016
Redecker, T.: The Most Difficult Problem Ever: Igo Hatsuyoron 120. Brett und Stein Verlag, Frankfurt am Main (2011). http://www.brett-und-stein.de/08-Impressum.php
Silver, D., Huang, A., Maddison, C., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., Dieleman, S., Grewe, D., Nham, J., Kalchbrenner, N., Sutskever, I., Lillicrap, T., Leach, M., Kavukcuoglu, K., Graepel, T., Hassabis, D.: Mastering the game of Go with deep neural networks and tree search. Nature 529(7587), 484–489 (2016)
Acknowledgements
Gerhard Knop was so kind to tell the author about his playing style on LittleGolem. Thanks to Manja Marz for her participation in the “Crazy Manja” experiments. Student Toni Strobel at Jena University helped by analysing “crazy analysis” histograms with respect to representation as the sum of overlapping normal distributions. Thanks to the editorial board and anonymous referees for their constructive criticism. Raphael Thiele was a disciplined proof reader and also helped with the LaTeX formatting.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Althöfer, I. (2016). Computer-Aided Go: Chess as a Role Model. In: Plaat, A., Kosters, W., van den Herik, J. (eds) Computers and Games. CG 2016. Lecture Notes in Computer Science(), vol 10068. Springer, Cham. https://doi.org/10.1007/978-3-319-50935-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-50935-8_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-50934-1
Online ISBN: 978-3-319-50935-8
eBook Packages: Computer ScienceComputer Science (R0)