Type A Strategy

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The Type A Strategy was coined in 1949 by Claude Shannon in his groundbreaking publication Programming a Computer for Playing Chess [1] as a brute-force strategy, which Shannon concluded would be both slow and a weak player, due to the average branching factor and the huge exponential explosion. He therefor favored to search only a small subset of plausible moves within a Type B strategy. However, with the advent of alpha-beta and all its enhancement, brute-force got very successful from the 70s until present, since the task of classifying and excluding "not plausible" moves, turned out to be quite difficult and error-prone.


from Shannon's Programming a Computer for Playing Chess:

A two-move strategy (based on considering all variations out to 2 moves) is given by
  Max  Min   Max    Min    f(M_ijkl M_ijk M_ij M_i P)
  M_i  M_ij  M_ijk  M_ijkl                                 . . . . (1)
A strategy of this sort, in which all variations are considered out to a definite number of moves and the move then determined form a formula such as will be called type A strategy. The type A strategy has certain basic weaknesses, which we will discuss later, but is conceptually simple, and we will first show how a computer can be programmed for such a strategy.
Unfortunately a machine operating according to the type A strategy would be both slow and a weak player. It would be slow since even if each position were evaluated in one microsecond (very optimistic) there are about 10^9 evaluations to be made after three moves (for each side). Thus, more than 16 minutes would be required for a move, or 10 hours for its half of a 40-move game.

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