Threat stacks to guide pruning and search extensions in shogi

In most cases game programs have to decide their next move under strict time constraints Iterative deepening is the most common method to make sure a move is played that is the result of a completed search to a certain depth To produce a reasonable move at each iteration a combination of pruning techniques and search extensions is used Often the decisions for pruning and extending the search are based on game speci c knowledge In this paper we propose to store the game speci c knowledge into threat stacks and use general rules regarding the content of these threat stacks for pruning and extension decisions Preliminary results in shogi show that if threat stacks are used instead of a standard quiescence search an improvement of the tactical performance can be expected