Artificial Intelligence by Ian Pratt (auth.)

By Ian Pratt (auth.)

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The resulting performance should be adequate (with that sort of look-ahead) against a casual human opponent. 3 More advanced considerations in game playing The approach to game-playing just outlined suffers from a number of limitations. For example, one problem is that it has no notion of a board situation which is interesting and worth investigating in detail. e, the initial board situation - nothing much is happening: moves by each player will lead to small changes in the utility of the current board state.

2 can be applied directly. It makes the program more fun to play if you can write a graphical interface. Once you have got the program working, you can investigate the effect of alpha-beta pruning. By counting the number of times that the condition a > f3 is or is not satisfied as the algorithm runs, you can determine the frequency of pruning. By playing the same game with alpha-beta pruning disabled, you can count the number of nodes that were pruned off.

E, the initial board situation - nothing much is happening: moves by each player will lead to small changes in the utility of the current board state. 7(b), by contrast, is much less stable. With successive moves, each side can loose a piece, resulting in much more rapid changes in the utility of the board states. A state in which the utility function does not change by large amounts from one side to another is called a quiescent state. 7(b); for it is in the second case that deep analysis is likely to be important.

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