AI based problem notes

1. Constraint
Satisfaction
Problem
• Artificial Intelligence

2. Constraint Satisfaction Problems (CSP)
Finding a solution that meets a set of constraints is the goal
of constraint satisfaction problems (CSPs), a type of AI
issue.
For tasks including resource allocation, planning, scheduling,
and decision-making, CSPs are frequently employed in AI.

3. Components
in CSP
 There are mainly three basic components in the constraint satisfaction
problem:
 Variables: {V1, V2, V3 … Vn}
 Set of Domains: {D1, D2, D3, … Dn} for each variable
 Constraints: The guidelines that control how variables relate to one
another are known as constraints.
 Ci = {Scope, Rel}
 Where scope is set of variables that participate in constraint
 Rel is relation that defines the values that variable can take.

4. Example.
 For instance, in a sudoku problem,
the restrictions might be that each
row, column, and 3×3 box can only
have one instance of each number
from 1 to 9.


5. CSP Solve using Backtracking
 V = {1, 2, 3, 4}
 D = {Red, Green, Orange}
 C = {1≠2, 1≠3, 1≠4, 2≠4, 3≠4}
1 2
3 4

6. CSP Solve using Backtracking
 V = {1, 2, 3, 4}
 D = {Red, Green, Orange}
 C = {1≠2, 1≠3, 1≠4, 2≠4,
3≠4}
1 2
3 4
1 2 3 4
Initial Domain R,G,O R,G,O R,G,O R,G,O
1=R R GO GO GO
2=G R G GO O
3=B R G O O

7. CSP Solve using Backtracking
 V = {1, 2, 3, 4}
 D = {Red, Green, Orange}
 C = {1≠2, 1≠3, 1≠4, 2≠4,
3≠4}
1 2
3 4
1 2 3 4
Initial Domain R,G,O R,G,O R,G,O R,G,O
1=R R GO GO GO
2=G R G GO O
3=G R G G O