Extended Null-Move Reductions
- Cite this paper as:
- David-Tabibi O., Netanyahu N.S. (2008) Extended Null-Move Reductions. In: van den Herik H.J., Xu X., Ma Z., Winands M.H.M. (eds) Computers and Games. CG 2008. Lecture Notes in Computer Science, vol 5131. Springer, Berlin, Heidelberg
In this paper we review the conventional versions of null-move pruning, and present our enhancements which allow for a deeper search with greater accuracy. While the conventional versions of null-move pruning use reduction values of R ≤ 3, we use an aggressive reduction value of R = 4 within a verified adaptive configuration which maximizes the benefit from the more aggressive pruning, while limiting its tactical liabilities. Our experimental results using our grandmaster-level chess program, Falcon, show that our null-move reductions (NMR) outperform the conventional methods, with the tactical benefits of the deeper search dominating the deficiencies. Moreover, unlike standard null-move pruning, which fails badly in zugzwang positions, NMR is impervious to zugzwangs. Finally, the implementation of NMR in any program already using null-move pruning requires a modification of only a few lines of code.
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