Next: About this document ...
Up: The Go-Playing Program Called
Previous: Discussion and future work
- 1
-
S. Ragab A. Abdelbar and S. Mitri.
Co-evolutionary particle swarm optimization applied to the 7x7
Seega game.
In Proc. of the IntJ. Conf. on Neural Networks, pages
243-248, Budapest, Hungary, July 2004.
- 2
-
B. Abramson.
Expected-outcome: A general model of static evaluation.
IEEE Transactions on Pattern Analysis and Machine
Intelligence, 12(2):182-193, 1990.
- 3
-
D. Benson.
Life in the game of Go.
Information Sciences, 10:17-29, 1976.
- 4
-
E. Bonabeau and G. Théraulaz.
Swarm smarts.
Scientific American, pages 72-79, March 2000.
- 5
-
B. Bouzy and B. Helmstetter.
Developments on Monte Carlo Go.
Advances in Computer Games 10, 2003.
- 6
-
B. Brügmann.
Monte Carlo Go.
Technical report, Syracuse University, March 1993.
ftp://ftp.cse.cuhk.edu.hk/pub/neuro/GO/mcgo.tex.
- 7
-
M. Sipser D. Lichtenstein.
Go is polynomial-space hard.
Journal ACM, 27(2):393-401, 1980.
- 8
-
T. Graepel D. Stern and D. MacKay.
Modelling uncertainty in the game of Go.
In Proc. of the Conference on Neural Information Processing
Systems, Vancouver, Canada, December 2004.
submitted.
- 9
-
D. Bump et al.
GNU Go home page, 2004.
http://www.gnu.org/software/gnugo/devel.html.
- 10
-
A. Huima.
Unsupervised learning of go patterns.
http://people.ssh.fi/huima/compgo/, 1999.
- 11
-
H. Hyötyniemi and P. Saariluoma.
Chess - Beyond the Rules.
Finnish Artificial Intelligence Society, 1999.
- 12
-
A. Iizuka.
AIGO home page, 2004.
http://www001.upp.so-net.ne.jp/iizuka/AIGO/.
- 13
-
T. Kageyama.
Lessons in the Fundamentals of Go.
Kiseido publishing company, 1978.
- 14
-
M. Müller.
Computer Go.
Special issue on games of Artificial Intelligence Journal,
2001.
- 15
-
T. Raiko.
Go81 home page, 2004.
http://www.cis.hut.fi/praiko/go81/.
- 16
-
T. Thomsen.
Lambda-search in game trees - with application to Go.
Computers and Games 2000, Lecture Notes in Computer Science,
2001.
Tapani Raiko
2005-05-10