By Philip J. Carter
A follow-up identify to Alan Wareham's "Brain Teasers", with over a hundred brain-teasing questions graded from effortless to very tricky. The authors have additionally written "Take the IQ attempt" and "Take the IQ problem" sequence.
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Additional info for Baffling Brain Teasers
If more than one promising sibling exist and the search space does not ﬁt into the TT, df-pn sometimes suffers from thrashing the TT by fast switches between subtrees. The 1 + e trick (Pawlewicz and Lew 2007) increases the threshold when 16 A. Kishimoto and M. Mueller df-pn selects the best child. This enables df-pn to stay longer in the subtree of one child, without frequently switching to other promising siblings. Given a proven node n, tree simulation (Kawano 1996) performs a quick proof check for an unknown node m that looks similar to n.
The proof and disproof numbers of the leaf node are always set to 1 in their original deﬁnition. However, in practice, some leaf nodes are easier to (dis)prove than others. With heuristic initialization, leaf nodes are heuristically initialized with proof and disproof numbers (Allis 1994). One example for this is using the number of legal moves at a leaf node, which can be calculated with little overhead in some games (Allis et al. 1994). Another popular approach is using domain-speciﬁc heuristic functions (Nagai 2002).
6(4), 293–326 (1975) R. Lake, J. Schaeffer, P. Lu, Solving large retrograde analysis problems using a network of workstations. Advances in Computer Games 7, 135–162 (1994) T. Lincke, Exploring the Computational Limits of Large Exhaustive Search Problems. PhD thesis, ETH Z€ urich, 2002 T. Marsland, A review of game-tree pruning. ICCA J. 9(1), 3–19 (1986) A. Nagai, A new depth-ﬁrst-search algorithm for AND/OR trees. Master’s thesis, The University of Tokyo, Tokyo, 1999 A. Nagai, Df-pn Algorithm for Searching AND/OR trees and its Applications.