By G. M. Adelson-Velsky, V. L. Arlazarov, M. V. Donskoy (auth.)
Algorithms for Games goals to supply a concrete instance of the programming of a two-person video game with whole details, and to illustrate a number of the tools of ideas; to teach the reader that it really is ecocnomic to not worry a seek, yet relatively to adopt it in a rational type, make a formal estimate of the size of the "catastrophe", and use all compatible capacity to maintain it right down to an inexpensive dimension. The e-book is devoted to the learn of equipment for proscribing the level of a seek. the sport programming challenge is especially well matched to the learn of the hunt challenge, and usually for multi-step answer approaches. With this in brain, the ebook makes a speciality of the programming of video games because the most sensible technique of constructing the guidelines and strategies provided. whereas a number of the examples are on the topic of chess, in simple terms an effortless wisdom of the sport is needed.
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Additional info for Algorithms for Games
Attempts to apply it even to positional features have not succeeded (the strong game of Samuel's program  for American checkers would appear to be unconnected with the fact that he used this concept in assigning weights to features). The second concept approaches the assignment of weights empirically. They are introduced as parameters in the program and after various games have been played the values chosen are those for which the program plays most strongly. It has also been proposed that an automatic process be set up, in which the values of the parameters change in the course of a single game.
Heuristic Methods coefficients in the functions i'j that define the type. Thus the value of the evaluation function for an arbitrary position A is given by ~(A) = M L ~iA)PiA). j-I Another way to develop a complex evaluation function, still within the framework of linear functions, is to use not only elementary features given a priori but also logical functions of them. An arbitrary function of the elementary predicates Pi ( A) (i = 1,2, . . , N) defined above can be defined in the same way. "'N be the value of the contemplated function for the arguments Pi(A) = £i' where £ takes on the values 0 or 1; then I q,(A) = I L L '1 =0 '2 =0 I L ~"'2 '" ,) PI(A) EN=O = £1 } & .
There also exist programs that correctly solve the problem of mate in a few moves or play correctly in simple endgames such as King and Pawns against King. On the Order in which Positions are Searched in the Game Tree Let us begin with algorithms for a search with pruning (the a, P heuristic). As we proved in Chapter 1, the minimum number of positions to be examined in the game tree 2l in order to establish the score of the base position Ao and the best initial move, is of the order of m k / 2 , where m is the mean number of moves at the positions to be examined and k is the depth of 2l .