Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
On the fairness and complexity of generalized k-in-a-row games
Theoretical Computer Science
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A new family of k-in-a-row games
ACG'05 Proceedings of the 11th international conference on Advances in Computer Games
Generating an opening book for amazons
CG'04 Proceedings of the 4th international conference on Computers and Games
| Hi-index | 0.00 |
An opening book is an important part in most game-playing computer programs. The so-called opening book is a database which contains an ocean of grandmaster's game records. Usually it is constructed manually by experts, or by selecting the excellent position from the massive raw game records by statistical. At the same time, some opening books can study and be optimized from new positions. But in connect6, it is impossible to construct an excellent opening book only by experiences from human beings. The reasons are: firstly, the average branch factor in Connect6 is huge; Secondly, the threat-based moves broadly existed in many positions, it makes the positions with small differences have opposite results. We use computer to generate the book automatically. This paper presents the way we construct the opening book of connect6, and the convenience it takes when we test the program.