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The Joy of Computer Chess (Levy, 1984)

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The Case for Using Probabilistic Knowledge in a Computer Chess Program (John L. Jerz)
Resilience in Man and Machine

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Take it from David Levy, the man who won every match he played against a computer for ten years. When it comes to today's computer games, the most challenging is an old favorite: chess! Now, in this up-to-the-minute, in-depth guide [1984 - not exactly up-to-the-minute anymore], he imparts intriguing knowledge about computer chess that's sure to make you a better player and a better programmer - whether you're a chess enthusiast, a computer buff, or both.
 
This excursion into artificial intelligence describes all the principles of chess programming - with examples from actual games - so everyone can understand them. It explains how chess computers are programmed, including ways to represent pieces, generate and evaluate moves, and perform quick "search strategies" that let the machine calculate a move's outcome - as well as initiate many exciting game variations.
 
You'll also learn many facts and techniques that will help you get the most from a chess computer:
  • insight into its current strengths and weaknesses (and how strong an opponent it could become)
  • how to use the chess computer to rate, monitor, and dramatically improve your game
  • exactly how to play against it - and maybe even beat it!
  • exhaustive advice on what to look for when buying a chess computer
  • analysis of some of the best man-versus-machine games ever played
  • and much more 

p.7 In order to be able to play chess well, a computer program need only know the rules of the game and how to evaluate any position which may arise. The rules of the game are not difficult to program, and are implicit in the legal move generator. What poses the real difficulty is the evaluation of chess positions.
 
p.8,10 After material, the next most important feature in chess is mobility. Mobility is the total number of moves that can be made by one's pieces, and this simple count provides an excellent measure of one's freedom of movement... experiments on the significance of mobility in chess have been carried out as long ago as 1949, when Eliot Slater published some statistics based on 78 randomly chosen master games... what is interesting is the almost consistent manner in which the winner's advantage in mobility increases as the game progresses.
 
p.59 It is clearly useful to devise ways of pruning the game tree. A human chess master can do this quite simply - he knows that certain moves "just cannot be right", so he ignores them. This reduced the size of his game tree to something between 50 and 100 positions. For a computer program, anything which helps to reduce the number of moves in the game tree is a boon, provided that it does not result in the program overlooking something vital... If the program's evaluation function were sufficiently accurate, it would be possible to reject moves simply on the basis that they lead to a position which is worse than the position currently under consideration.
 
p.75 One of the most controversial aspects of computer chess is the question of whether or not a computer program can eventually be stronger than the (human) World Chess Champion... No-one knows the answer to this question. My own opinion is that it will be between the years 1995 and 2000 when a computer program can play at the level of a strong Grandmaster under tournament conditions.
 
p.76-77 An increase in the number of nodes examined per move is usually reflected in an increase in the program's tactical ability. A program might well improve tactically by 100 points, but as a player becomes stronger, tactics play a smaller part in determining the results of his games. At the very top level, in the World Championship matches (for humans), only a very small proportion of the games are decided by tactics. Hence, improving a program's tactics will not result in an overall improvements in its play to the same extent.
 
p.82 The syndrome known as the Horizon Effect manifests itself in positions in which a program cannot see some crucial move because that move is beyond the horizon of its look-ahead analysis. As a result of this short sightedness, the program makes a serious error. [JLJ - therefore, machines must check to verify that the position is resilient before making a search cut-off]

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