Artificial IntelligenceA revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. |
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Page 89
... constraints , which says that each number may correspond to only one letter and that the sums of the digits must be as they are given in the problem , is first ... constraints to be inferred from the ones 3.5 . CONSTRAINT SATISFACTION 89.
... constraints , which says that each number may correspond to only one letter and that the sums of the digits must be as they are given in the problem , is first ... constraints to be inferred from the ones 3.5 . CONSTRAINT SATISFACTION 89.
Page 90
... Constraint propagation terminates for one of two reasons . First , a contradiction may be detected . If this happens , then there is no solution consistent with all the known constraints . If the contradiction involves only those ...
... Constraint propagation terminates for one of two reasons . First , a contradiction may be detected . If this happens , then there is no solution consistent with all the known constraints . If the contradiction involves only those ...
Page 301
... Constraints Much of what we know about the world can be represented as sets of constraints . We talked in Section 3.5 about a very simple problem , cryptarithmetic , that can be described this way . But constraint - based ...
... Constraints Much of what we know about the world can be represented as sets of constraints . We talked in Section 3.5 about a very simple problem , cryptarithmetic , that can be described this way . But constraint - based ...
Contents
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
Copyright | |
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Abbott agents algorithm answer apply approach ARMEMPTY assertions attributes axioms backpropagation backtracking backward belief best-first search breadth-first search Caesar called Chapter chess clauses complete concept conceptual dependency consider constraints contains contradiction corresponding define depth-first depth-first search described discussed domain example fact function game tree goal grammar graph heuristic Horn clauses important inference inheritance input instance interpretation isa links John justification knowledge base knowledge representation labeled learning Marcus match minimax move MYCIN natural language node object ON(B ON(C operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG represent result robot rules script Section semantic semantic net sentence shown in Figure simple slot solution solve specific step structure Suppose syntactic task techniques theorem things tree truth maintenance system understanding variables version space