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Constraint Satisfaction Problems - 1 in AI

Instructional Objective
  • The students will be introduced to the class of constraint satisfaction problems.
  • They will learn how to express different constraint formally.
  • They will learn how to model CSP problems as search problems, and how DFS can be used with backtracking to solve these problems.
  • They will learn how to cast different CSP problem to search problems.
Introduction

Many problems in AI are types of constraint satisfaction problems.
  • Satisfiability
  • Scheduling
  • Timetabling
  • Supply chain management
  • Graph colouring
  • Machine vision
  • Puzzles
Constraint Satisfaction Problems

A CSP consists of :
  - a set of variables, X
  - for each variable xi in X, a domain Di
  • Di is a finite set of possible values
 - a set of constraints restricting tuples of values
  • if only pairs of values, it's a binary CSP
A solution is an assignment of a value in Di to each variable xj such that every constraints satisfied

Colouring as CSP
  • Can we colour all 4 regions with 3 colours so  that no two adjacent regions are the same colour?



  • Variable for each node
     - All Di = {red, green, blue}
  • Constraint for each edge
     - all constraints of the form 
            xi  ≠ xj
  • Solution gives a colouring
  • It's a binary CSP


SAT as a CSP
  • Variable in CSP for each variable/letter in SAT
  • Each domain Di = {true, false}
  • Constraint corresponds to each clause
        - disallows unique tuple which falsifies clause
        - e.g. (not A) or (B) or (not C)
               ⇒ not < A = true, B = false, C = true >
  • Not binary CSP unless all clauses 2-clauses
N-Queens as a CSP
  • Chessboard puzzle
      - place 8 queens on a 8x8 chessboard so that no two attack each other
  • Variable xi for each row i of the board
  • Domain = {1,2,3.....,n} for position in row


Formal Definition of Constraints

A constraint Cijk.... involving variables xi, xj, xk ...
  - is any subset of combination of values from Di, Dj, Dk ....
  - i.e. Cijk ... ⊆ Di x Dj x Dk...
   - indicating the allowed set of values
A number of ways to write constraints:
  - e.g. if D1 - D2 = {1,2,3} ...
  •     { (1,2), (1,3), (2,1), (2,3),(3,1),(3,2)}
  • x1 ≠ x2 
More Complex Constraints


 

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