Turing A, Strachey C, Bates M, and Bowden B. Digital computers applied to games. In Bowden B, editor, Faster than thought, pages 286--310. Pitman, 1953.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....of backgammon, bridge, checkers, chess, Othello, poker, and Scrabble are presented. They are the recipes for building high performance game playing programs. 1 Introduction Arthur Samuel is one of the pioneers of arti cial intelligence research. Together with Claude Shannon [1] and Alan Turing [2], he laid the foundation for building high performance game playing programs. Samuel is best known for developing his checkers program. Over his career, he consistently sold his work as research in machine learning. His papers describing the program and its learning capabilities are classics in ....

A. Turing. Digital computers applied to games. In B. Bowden, editor, Faster than Thought, pages 286-295. Pitman, 1953.

....with mini max search[Levy91] usually with some form of tree pruning such as alpha beta cut off[Knuth75] to reduce the number of moves considered. A board evaluation function is used for the terminal boards at the horizon (or leaf nodes) of the search tree. The principle of hotpursuit [Turing53] is usually used so that the search tree is locally extended to ensure that the boards which are evaluated by the boardevaluation function are relatively stable boards and are not so badly effected by the horizon effect[Berliner73] This principle essentially causes all pending takes, for example, ....

....before a board is considered for the purposes of static board evaluation. This is particularly important in draughts since the rules of the game dictate that take moves must be carried out by a player if any are available on a board. For more details of these issues see the papers of Turing[Turing53] and Shannon [Shannon50b] which discuss algorithms for playing computer chess, which all equally apply to draughts. The static board evaluation function is essentially a weighted sum of features score based on the various properties of the board. The board features considered when evaluating a ....

A.M. Turing, "Digital Computers Applied to Games", Faster Than Thought (Ed. B.V. Bowden), pp 186-310, 1953.

....little account of learning are inadequate accounts of human cognition. Instead we present an alternative thesis on cognition which places learning at the centre of what it is to be intelligent, rather than placing problem solving at the centre. Interestingly, this is a view much nearer to Alan Turing s thought (1953), than his Turing machine conception of computation. Turing wanted to know not only how machines could solve problems, but how they could learn. Certainly SOAR places great impotance on learning, but it is in our view an impoverished view of learning to see it only as search within a problem ....

Turing A.M. (1953), Digital Computers applied to games.

....acts as an evaluation function that can be applied to every node in the tree, not just quiescent nodes. This allows the analysis to assume a fixed depth search, rather than the variable depth that results from the capture tree. The importance of quiescence was realized by Shannon [58] and Turing [66] and experimentally verified by Gillogly [19] for the game of chess. Unfortunately, this procedure has only been shown to be beneficial in games like chess. There are many games in which a capture is not even a legal move, and it is difficult to identify a quiescent position. III.D The Consistency ....

A. M. Turing. Digital computers applied to games. In B. V. Bowden, editor, Faster than Thought: A Symposium on Digital Computing Machines, pages 286-- 310. Sir Isaac Pitman and Sons, Ltd., London, 1953.

....If a min move happens to be forced in a max strategy this fact does not influence max depth max depth is only measuring the options of the max player. The idea that forced lines of play should be explored more deeply goes back to the original chess papers of Shanon and Turing [Shanon, 1950] [Turing et al. 1953]. It is one of the justifications for the value of quiescence search in chess. It also clearly underlies the use of check extensions. It is also the motivation for the singular extension heuristic [Anantharaman et al. 1990] However, we believe that effective use of these heuristics has been ....

....of the conspiracy depth principle. 9. 1 Quiescence Search and Capture Extensions Shanon and Turing, in the earliest papers on computer chess, suggested that forced variations should be searched beyond the horizon, i.e. to a depth greater than the nominal ply depth of the search [Shanon, 1950] [Turing et al. 1953]. The most immediately successful implementation of this idea has become known as quiescence search. As defined in section 8, the quiescence value of a position is the value computed from searching the stand pat or capture tree from that position at each position the player to move can either ....

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A. M. Turing, C. Strachey, M. A. Bates, and B. V. Bowden. Digital computers applied to games. In B. V. Bowden, editor, Faster than Thought, pages 286--310. Pitnam, 1953.

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Turing A, Strachey C, Bates M, and Bowden B. Digital computers applied to games. In Bowden B, editor, Faster than thought, pages 286--310. Pitman, 1953.

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Alan M. Turing, Christopher Strachey, M. A. Bates, and Bertram V. Bowden. Digital computers applied to games. In B. V. Bowden, editor, Faster Than Thought, pages 286-310. Pitman, London, 1953.

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Turing A, Strachey C, Bates M, and Bowden B. Digital computers applied to games. In Bowden B, editor, Faster than thought, pages 286--310. Pitman, 1953.

No context found.

A. M. Turing, C. Strachey, M. A. Bates, and B. V. Bowden. Digital computers applied to games. In B. V. Bowden, editor, Faster Than Thought, pages 286{ 310. Pitman, London, 1953.

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A.M. Turing, C. Strachey, M.A. Bates and B.V. Bowden, "Digital Computers Applied to Games" in B.V. Bowden, ed., Faster Than Thought, Pitman, 1953, 286-310. -

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