Full Description
Much of AI research is about problem-solving strategies, and
several techniques have been crystalized. One such technique
is constraint satisfaction or reasoning based on relations.
Constraint-based reasoning is used to solve a wide field of
problems, and recently constraint techniques have been
incorporated into logic programming languages, yielding a
whole new field of research and application: constraint
logic programming. Constraint satisfaction techniques have
become part of almost all introductory books on AI.
This monograph is about constraint satisfaction. It differs
from others in that it presents all approaches under a
common, generalizing view: dynamic constraints. This new way
of viewing constraints provides new insights about the
different approaches, and forms a very practical basis for
teaching constraint-based reasoning. A uniform view of the
constraint world is also a good basis for constraint
research. This text is not intended to be a self-contained
textbook on constraint-based reasoning, but rather a
coherent text on an interesting view of the field.
Contents
The office world.- Constraint concepts.- Constraint relaxation.- Backtracking approaches.- From simple filtering to tagging.- Appoaches to filtering in parallel.- Optimization approaches.- Instead of a conclusion.
