Computer Games IISpringer New York, 1988 M06 24 - 546 páginas Long before the advent of the electronic computer, man was fascinated by the idea of automating the thought processes employed in playing games of skill. The very first chess "Automaton" captured the imagination oflate eighteenth century Vienna, and by the early 1900s there was a genuine machine that could play the chess endgame of king and rook against a lone king. Soon after the invention of the computer, scientists began to make a serious study of the problems involved in programming a machine to play chess. Within a decade this interest started to spread, first to draughts (checkers) and later to many other strategy games. By the time the home computer was born, there had already been three decades of research into computer games. Many of the results of this research were published, though usually in publications that are extremely difficult (or even impossible for most people) to find. Hence the present volumes. Interest in computers and programming has now reached into almost every home in the civilized world. Millions of people have regular access to computers, and most of them enjoy playing games. In fact, approximately 80 percent of all software sold for use on personal computers is games software. |
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David N.L. Levy. The types of levels higher than point and string cannot be defined clearly . Human players cannot be ... definition for those concepts . Thus , as the human players refine their recognition of the board situation in ...
David N.L. Levy. The types of levels higher than point and string cannot be defined clearly . Human players cannot be ... definition for those concepts . Thus , as the human players refine their recognition of the board situation in ...
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... defined by a given point and a given size ; GrpName ( P ) returns the identifier of the group which includes the point P ; and Vitality ( X ) returns an approximate value of the vitality of an object X ( the accuracy is not defined in ...
... defined by a given point and a given size ; GrpName ( P ) returns the identifier of the group which includes the point P ; and Vitality ( X ) returns an approximate value of the vitality of an object X ( the accuracy is not defined in ...
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... defined feature : " the maximum number of played pieces of the same color in a possible winning 5 - pattern which includes the move . " The possible values of this feature are 1 , 2 , 3 or 4. The relation " better than " might be taken ...
... defined feature : " the maximum number of played pieces of the same color in a possible winning 5 - pattern which includes the move . " The possible values of this feature are 1 , 2 , 3 or 4. The relation " better than " might be taken ...
Contenido
by ALAN M STANIER | 12 |
by ALAN M STANIER | 21 |
CHAPTER 3 | 32 |
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Términos y frases comunes
5-pattern abcdefgh adjacent algorithm analysis artificial intelligence basic block board position board situation branch branching factor called capture chess color complete components computer chess Computer Go configuration considered corner data structure decision described discs dominoes draw edge endgame evaluation function example expert Figure game tree games played given Go game Go player Go program Go-Moku goal Gopal half-moves Hand 2 Hand heuristic high-card points human players IAGO IAGO's initial Jonathan Cerf joseki learning legal moves lens linkage list of subgoals look-ahead machine minimax Move number msec node opponent opponent's optimal Othello pair pass perception pieces points poker possible moves problem REVERSI routine rules Santa Cruz Open schema score selection sequence square stable strand strategy string tactical techniques territory Theorem tournament Trick tsumego update vacant weighting factors winning