Constraint Satisfaction Problems (CSPs) are a class of problems where the goal is to find a solution that satisfies a set of constraints.
Thank you for reading this post, don't forget to subscribe!- A solution assigns values to variables such that all constraints are satisfied.
Components:
- Variables: The unknowns to be solved (e.g., cells in Sudoku).
- Domains: Possible values for each variable (e.g., numbers 1-9 in Sudoku).
- Constraints: Rules that define valid combinations of variables (e.g., no repeating numbers in a row or column in Sudoku).
Algorithms:
- Backtracking: Systematically tries all possible assignments and backtracks when a constraint is violated.
- Constraint Propagation: Reduces the search space by enforcing constraints early.
Example:
- Solving a Sudoku puzzle involves assigning numbers to cells such that all rows, columns, and subgrids contain unique numbers.