By means of so-called virtual or shadow prices, short-run factor demands, short-run marginal costs, etc. can be derived from any long-run cost function. The traditional approach (short-run/restricted/conditional/variable cost functions) is criticized, and it is also shown that technological change, scale e!ects, etc. can be added to any cost function by means of disembodied factor-augmenting e$ciency indexes, easing the interpretations of the e!ects, but without loss of #exibility. It is shown that the trend-and scaleparameters of the (long-run) translog cost function can be directly translated into trendand scale-parameters of such e$ciency indexes. The techniques are illustrated on the well-known Berndt}Wood data set, using a (Diewert) long-run generalized Leontief (GL) cost function, and assuming that capital and labour are quasi-"xed.2000 Published by Elsevier Science S.A. All rights reserved.JEL classixcation: D21; D24; D45; E23
Abstract. This paper proposes a new method for searching two-valued (binary) game trees in games like chess or Go. Lambda-search uses null-moves together with different orders of threat-sequences (so-called lambda-trees), focusing the search on threats and threat-aversions, but still guaranteeing to find the minimax value (provided that the game-rules allow passing or zugzwang is not a motive). Using negligible working memory in itself, the method seems able to offer a large relative reduction in search space over standard alpha-beta comparable to the relative reduction in search space of alpha-beta over minimax, among other things depending upon how non-uniform the search tree is. Lambda-search is compared to other resembling approaches, such as null-move pruning and proof-number search, and it is explained how the concept and context of different orders of lambda-trees may ease and inspire the implementation of abstract game-specific knowledge. This is illustrated on open-space Go block tactics, distinguishing between different orders of ladders, and offering some possible grounding work regarding an abstract formalization of the concept of relevancy-zones (zones outside of which added stones of any colour cannot change the status of the given problem).
Abstract. This paper proposes a new method for searching two-valued (binary) game trees in games like chess or Go. Lambda-search uses null-moves together with different orders of threat-sequences (so-called lambda-trees), focusing the search on threats and threat-aversions, but still guaranteeing to find the minimax value (provided that the game-rules allow passing or zugzwang is not a motive). Using negligible working memory in itself, the method seems able to offer a large relative reduction in search space over standard alpha-beta comparable to the relative reduction in search space of alpha-beta over minimax, among other things depending upon how non-uniform the search tree is. Lambda-search is compared to other resembling approaches, such as null-move pruning and proof-number search, and it is explained how the concept and context of different orders of lambda-trees may ease and inspire the implementation of abstract game-specific knowledge. This is illustrated on open-space Go block tactics, distinguishing between different orders of ladders, and offering some possible grounding work regarding an abstract formalization of the concept of relevancy-zones (zones outside of which added stones of any colour cannot change the status of the given problem).
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