A Constraint Satisfaction Problem consists of: (1) a set of variables X = {X₁, X₂, ..., Xₙ}; (2) a domain D for each variable specifying possible values; (3) a set of constraints C restricting variable combinations. The goal is finding an assignment of values to variables satisfying all constraints. Solution techniques include: backtracking search, forward checking, arc consistency algorithms (AC-3), constraint propagation, and variable/value ordering heuristics (most constrained variable, least constraining value). CSPs model: scheduling, resource allocation, configuration problems, graph coloring, and Sudoku. When optimization is needed, CSPs extend to Constraint Optimization Problems (COPs).