Constraint satisfaction is a problem-solving approach used in fields like computer science and artificial intelligence. It involves finding values for variables that meet specific conditions or constraints. For example, in a scheduling problem, the goal might be to assign time slots to tasks without overlapping. In constraint satisfaction problems, each variable has a domain of possible values, and constraints define the relationships between these variables. Techniques such as backtracking and constraint propagation are often employed to efficiently explore the solution space. Common applications include Sudoku, map coloring, and resource allocation.