Unit 3: Constraint Satisfaction
AI applications are built upon the idea of a problem statement with constraints. In AI, we must work within those constraints in order to develop an optimal solution. In this unit, we will define "problem" in specific AI terms and discuss different approaches to constraint satisfaction. Constraint satisfaction is an important subject area within AI. The famous Map Coloring Problem has simple variables and simple constraints and is thus useful in illustrating the basics of constraint satisfaction. By the end of this unit, you will be able to solve basic problems.
Completing this unit should take you approximately 10 hours.
3.1: Problem Definition and Approaches
Read these slides. CSP stands for Constraint Satisfaction Problems, which include, for example, problems in task scheduling, planning robot actions, solving puzzles (for example, the classic N-Queens Problem and the Four Color Problem), and interpreting sensory data.