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Constraint Satisfaction Problems - Assignment 4

This repository presents implementations of four classical problems based on the concept of Constraint Satisfaction Problems (CSP) in Artificial Intelligence.

Problems Included

  1. Australia Map Coloring
  2. Telangana District Map Coloring
  3. Sudoku Solver
  4. Cryptarithmetic Puzzle (TWO + TWO = FOUR)

All problems are solved using a backtracking approach, ensuring that constraints are satisfied at every step.


Understanding CSP

A Constraint Satisfaction Problem consists of:

  • Variables: Elements that need values
  • Domain: Possible values for each variable
  • Constraints: Conditions that must be satisfied

The aim is to assign values to all variables without violating any constraint.


Approach Used

  • Backtracking Search
  • Constraint Checking before assignment
  • Recursive exploration of possibilities

Applications

CSP techniques are widely used in:

  • Scheduling systems
  • Puzzle solving
  • Resource allocation
  • AI planning problems

Summary

This assignment demonstrates how CSP techniques can be applied to solve structured problems efficiently using logical constraints and systematic search.

About

AI-based Constraint Satisfaction Problem implementations featuring Map Coloring, Sudoku solving, and Cryptarithmetic puzzles using efficient backtracking techniques.

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