Computer Games IILong 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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Página 171
We no longer have to keep track of the capture count and the net number of
passes . This allows us to omit the number under the boards in tree diagrams like
Figure 13 . Corollary 3 also shows us at once , without computing the tree in
Figure ...
We no longer have to keep track of the capture count and the net number of
passes . This allows us to omit the number under the boards in tree diagrams like
Figure 13 . Corollary 3 also shows us at once , without computing the tree in
Figure ...
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This is indicated in Figure 14 , which shows only a subtree with an optimal Black
strategy and all White responses . Figure 15 is a similar subtree for 1 x 5 Go . An “
J ” indicates a forced move , i . e . , the alternatives are “ obviously ” worse .
This is indicated in Figure 14 , which shows only a subtree with an optimal Black
strategy and all White responses . Figure 15 is a similar subtree for 1 x 5 Go . An “
J ” indicates a forced move , i . e . , the alternatives are “ obviously ” worse .
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Web Perception in Operation Two brief examples will help to show how the web
perception system works in a game context . Figure 5 shows the web for the
White stone at c8 in the game situation originally introduced in Figure 1 . As in
Figure ...
Web Perception in Operation Two brief examples will help to show how the web
perception system works in a game context . Figure 5 shows the web for the
White stone at c8 in the game situation originally introduced in Figure 1 . As in
Figure ...
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added analysis arrangement attack basic Black block branch called chess complete components configuration connected considered created data structure decision defined described determined developed discs discussed draw edge effect element evaluation example expert fact factors Figure final forcing four function further given gives goal Hand heuristic holds human important initial interesting knowledge lead learning linkage look look-ahead machine means method move node Note object opening opponent particular pass pattern pieces planning play player points position possible present probability problem reasonable recognize represent routine rules score selection sequence shows side simple situation specific square stones strategy string structure subgoals success suit tactical territory tree Trick turn weighting White winning