Parallel retrograde analysis on a distributed system
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
External memory algorithms and data structures: dealing with massive data
ACM Computing Surveys (CSUR)
Games solved: now and in the future
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Construction of Chinese Chess Endgame Databases by Retrograde Analysis
CG '00 Revised Papers from the Second International Conference on Computers and Games
Delayed duplicate detection: extended abstract
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Knowledge Inferencing on Chinese Chess Endgames
CG '08 Proceedings of the 6th international conference on Computers and Games
Knowledge abstraction in Chinese chess endgame databases
CG'10 Proceedings of the 7th international conference on Computers and games
Conflict resolution of chinese chess endgame knowledge base
ACG'09 Proceedings of the 12th international conference on Advances in Computer Games
Aggregating consistent endgame knowledge in Chinese Chess
Knowledge-Based Systems
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This paper gives a new sequential retrograde analysis algorithm for the construction of large endgame databases that are too large to be loaded entirely into the physical memory. The algorithm makes use of disk I/O patterns and saves disk I/O time. Using our algorithm we construct a set of Chinese-chess endgame databases with one side having attacking pieces. The performance result shows that our algorithm works well even when the number of positions in the constructed endgame is larger than the number of bits in the main memory of our computer. We built the 12-men database KCPGGMMKGGMM, the largest database reported in Chinese chess, which has 8,785,969,200 positions after removing symmetrical positions on a 2.2GHz P4 machine with 1 GB main memory. This process took 79 hours. We have also found positions with the largest DTM and DTC values in Chinese chess so far. They are in the 11-men database KCPGGMKGGMM; the values are 116 and 96, respectively.