Controlled Conspiracy-Number Search

In this paper we present a new conspiracy number search algorithm (CNS), called Controlled Conspiracy Number Search (CCNS). The basic steps of any CNS algorithm, the selection, the expansion, and the backup of results have been modiied compared to other CNS algorithms. The selection is done by assigning demands, so called CN targets, to the nodes of the tree in a top-down fashion. By this, a set of leaves is selected in a single selection phase. The expansion is used to check, whether or not a leaf node can fullll its demand. The backup uses heuristic information gained from the expansion step to prepare the tree for the next selection phase. As a result, our algorithm is stronger than the-algorithm in tactical positions. This is shown by comparing them on a set of test positions. It is able to play even in nontactical positions, as shown on the 4:IPC 3 ; where Ulysses CCN, a program based on the CCNS algorithm, played a complete tournament. In addition, since in every selection step a set of leaves is selected for expansion, the algorithm may be well suited for parallelization.

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