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By Edward Tsang, Thom Fruehwirth

This textbook examines the constraint delight challenge (CSP), that is a basic challenge in AI functions. It goals to supply a entire advent to the CSP, protecting theoretical, sensible and implementation concerns. The e-book discusses formal definitions, CSP fixing algorithms and implementation of a few of the algorithms on PROLOG. the most aim of this publication is to spot the houses of CSPs and introduce algorithms for tackling CSP. Its major characteristic is the truth that it provides the data in CSP-solving in a single quantity.

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Foundations of Constraint Satisfaction

This textbook examines the constraint delight challenge (CSP), that's a normal challenge in AI functions. It goals to supply a finished creation to the CSP, masking theoretical, useful and implementation matters. The publication discusses formal definitions, CSP fixing algorithms and implementation of a few of the algorithms on PROLOG.

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General methods It is generally believed that efficiency can be gained by encoding domain specific knowledge into the problem solver. For example, after careful analysis of the Nqueens problem, one can find algorithms which solve it very efficiently [AbrYun89, Bern91]. However, there are good reasons for studying general algorithms. First, tailor made algorithms are costly. Second, tailored algorithms are limited to the problems for which they are designed. A slight change of the problem specification would render the algorithm inapplicable.

In early research in planning, the world is simplified in such a way that all events are assumed to be instantaneous. In that case, three relations are possible between any two events A and B: “A before B”, “B before A” or “A equals B”. Allen [1983] points out that when durations in events are reasoned about, 13 relations are possible between any two events. 10. 5 Examples and Applications of CSPs 25 In planning and scheduling, one has to determine the temporal relationship between events. There are basically two approaches.

Problem reduction could be performed at any stage of the search. Various search strategies combine problem reduction and search in various ways (described in detail in Chapters 5 to 7). Some of these strategies have been proved to be extremely effective. 42 CSP solving — An overview In general, the more redundant values and compound labels one attempts to remove, the more computation is required. One the other hand, the less redundant values and compound labels one removes, the more time one is likely to spend in backtracking.

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