| For class on | Reading |
|---|---|
| 1/14/2009 |
C. Thompson. Halo 3: How Microsoft Labs Invented a New Science of Play. Wired 15(09).
|
| 2/16/2009 |
P. Auer, N. Cesa-Bianchi, P. Fischer. Finite-time Analysis of the Multiarmed Bandit Problem. Machine Learning 47(2-3), pp. 235-256. May, 2002.
J. Vermorel, M. Mohri. Multi-Armed Bandit Algorithms and Empirical Evaluation.
In 16th European Conference on Machine Learning (ECML 2005).
Lecture Notes in Computer Science 3720,
J.G. Crbonell, J. Siekmann (eds.).
pp. 437-448. 2005. |
| 2/27/2009 |
R. Hearn. Tipover is NP-complete. Mathematical Intelligencer, 2006, 28(3), pp. 10-14.
|
| 3/23/2009 |
G. Chaslot, S. Bakkes, I. Szita, P. Spronck. "Monte-Carlo Tree Search: A New Framework for Game AI." Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference (eds. M. Mateas and C. Darken), pp. 216-217. AAAI Press.
L. Kocsis, C. Szepesvari. Bandit based Monte-Carlo Planning. In 15th European
Conference on Machine Learning, pp. 282-293, 2006.
|
P. Woodward. "Yahtzee: The Solution." Chance 16, No. 1, 18-22, 2003
Available from the Loyola/Notre Dame Library
J. Glenn. "An Optimal Strategy for Yahtzee." Loyola College in Maryland,
Department of Computer Science, Technical Report CS-TR-0002, May 2006.
Local PDF
J. Glenn. "Computer Strategies for Solitaire Yahtzee." In 2007 IEEE
Symposium on Computational Intelligence and Games.
Local PDF
IEEE Explore
J. Glenn, H.-r. Fang, C. Kruskal.
A retrograde approximation algorithm for one-player Can't Stop.
In 5th International Conference on Computers and Games (CG2006).
Lecture Notes in Computer Science 4630,
H.J. van den Herik, P. Ciancarini, H.H.L.M. Donkers (eds),
pp. 148-159. 2006.
Local PDF
SpringerLink
D. Billings, A. Davidson, J. Schaeffer, D. Szafron. "The Challenge of Poker."
Artificial Intelligence Journal, 134(1-2), pp. 210-240, 2002.
U. of Alberta PDF
A. Nagai. A new AND/OR tree search algorithm using proof number and disproof number. In Proceesings of Game Programming Workshop, pp. 40-45.