By Edward Tsang, Thom Fruehwirth
This textbook examines the constraint delight challenge (CSP), that is a basic challenge in AI purposes. It goals to supply a finished advent to the CSP, protecting theoretical, useful and implementation concerns. The publication discusses formal definitions, CSP fixing algorithms and implementation of a few of the algorithms on PROLOG. the most target of this e-book is to spot the homes 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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5(b)). 5(a) are w, x, y and z. Assume that we are allowed to label the map with three colours only: r (for red), g (for green) and b (for blue). e. 5(b) specify the domain. 5(b) represents a constraint which states that the connected nodes must not take the same value. The constraint on variables A and B (denoted CA,B) is conceptually seen as the set {(
7. Given any junction independent of the scene, there are limited choices of labels. 8. One way in which to formalize the scene labelling problem as a CSP is to use one variable to represent the value of a line in the scene. 9. The domain of each variable is therefore the set {+, −, →, ←}. 8) impose constraints on the variables. 8, the values that these three variables can take simultaneously are restricted to: F A F + G (
An undirected graph is a tuple (V, E) where V is a set of nodes and E is a set of edges, each of which being a collection of exactly two elements in V. ■ The nodes in an arc are ordered whereas the nodes in an edge are not. An edge can be seen as a pair of arcs (x,y) and (y,x). A binary CSP is often visualized as a constraint graph, which is an undirected graph where the nodes represent variables and each edge represents a binary constraint. Definition 1-16: For all graphs (V, E), node x is adjacent to node y if and only if (x, y) is in E: ∀ graph((V, E)): (∀x, y ∈ V: adjacent(x, y, (V, E)) ≡ (x, y) ∈ E) ■ Definition 1-17: A hypergraph is a tuple (V, E) where V is a set of nodes and E is a set of hyperedges, each of which is a set of nodes.