![]() ![]() To improve the performance of the Solver, the final implementation included two heuristics to deal with variable ordering, which are explained further in the Heuristics sub-section. The first implementation of the Solver used static variable (and value) ordering. In each stage, the algorithm picks a variable (position) to fill next and then begins testing each of its possible values, exploring and evaluating each assignment. If the current assignment is not consistent (does not adhere to the constraints), the algorithm backtracks to the last known consistent state and tries a different path. In each iteration, the Solver checks that the assignment is consistent, i.e. It uses a depth-first search that is capable of exploring and evaluating assignments, which can now be thought of as nodes. The Solver makes use of a backtracking search algorithm, as explained in Norvig and Russel's Artificial Intelligence: A Modern Approach. C = "Each value appears once in each row, column and 3x3 block of the grid" is the set of constraints.A set of variables, X = is the domain describing the values each variable can be assigned ( X i ∈ D), and.Ĭonstraint satisfaction problems can be recognised by the presence of: Constraint Satisfaction Problems (CSP)Ī constraint satisfaction problem (CSP) is a problem that involves a number of variables which can be assigned multiple values, based on some constraints. ![]() Please note that throughout this readme the terms position, cell and variable are used interchangeably. A puzzle is completed when each position has been assigned a value, such that each value appears once per row, column, and 3x3 block of the grid. Each position, also called a cell, can hold a value between 1 and 9. Sudoku is a logic-based, number-placement puzzle, where each board consists of a 9x9 grid with a some fixed values. The implementation incorporates heuristic functions to make informed decisions when choosing which move to make next. This project is an agent capable of solving Sudoku puzzles of varying difficulties using a backtracking search, by combining depth-first search and constraint propagation. ![]()
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