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In: Twentieth National Conference on Artificial Intelligence (AAAI 2005), pp. : NCTU6 Wins Man-Machine Connect6 Championship 2009. : Parallel alpha-beta search on shared memory multiprocessors. : Df-pn Algorithm for Searching AND/OR Trees and Its Applications. : Improving depth-first PN-search: 1 + ε trick. ) CG 2006. LNCS, vol. 4630, pp. 160– 171. -C. Wu et al. : Superlinear Speedup in State-space Search. V. ) FSTTCS 1988. LNCS, vol. 338, pp. 161–174. : Randomized Parallel Proof-Number Search.

1 Introduction Most modern game-playing computer programs successfully apply αβ search with enhancements for online game-playing. However, the enhanced αβ search is sometimes not sufficient to play well in the endgame. In some games, such as Chess, this problem is solved by the use of endgame databases. Due to memory constraints this is only feasible for endgames with a relatively small state-space complexity. An alternative approach is the use of a specialized binary (win or non-win) search method, such as Proof-Number (PN) search [2].

However, adding heuristic knowledge may guide PN search through these difficult positions. To find some truth for this statement we performed a new experiment. PN2 and EF-PN2 were used to compute the game-theoretic value of 6 × 6 LOA. Especially in the beginning of this game, there are hardly any forcing moves. In passing, we remark that this game was already solved by PN2 in 2008 [14]. For this experiment, symmetry was taken into account to prevent redundancy. The parameter setting of EF-PN2 was the same as in the previous subsection.

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