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Breaking Symmetry in Matrix Models of Constraint Satisfaction ProblemsPowerPoint Presentation

Breaking Symmetry in Matrix Models of Constraint Satisfaction Problems

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Breaking Symmetry in Matrix Models of Constraint Satisfaction Problems

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Breaking Symmetryin Matrix Models ofConstraint Satisfaction Problems

Alan M. Frisch

Artificial Intelligence Group

Department of Computer Science

University of York

Co-authors

Ian Miguel, Toby Walsh, Pierre Flener, Brahim Hnich, Zeynep Kiziltan, Justin Pearson

Acknowledgement

Warwick Harvey

An instance of the CSP consists of

- Finite set of variables X1,…,Xn, having finite domains D1,…,Dn.
- Finite set of constraints. Each restricts the values that the variables can simultaneously take. Example: x neq y. x+y<z.

- A total instantiation maps each variable to an element in its domain.
- A solution to a CSP instance is a total instantiation that satisfies all the constraints.
- Problem: Given an instance
- Determine if it is satisfiable (has a solution)
- Find a solution
- Find all solutions
- Find optimal solution

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Week 1

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Period 1

0 vs 1

0 vs 2

4 vs 7

3 vs 6

3 vs 7

1 vs 5

2 vs 4

Period 2

2 vs 3

1 vs 7

0 vs 3

5 vs 7

1 vs 4

0 vs 6

5 vs 6

Period 3

4 vs 5

3 vs 5

1 vs 6

0 vs 4

2 vs 6

2 vs 7

0 vs 7

Period 4

6 vs 7

4 vs 6

2 vs 5

1 vs 2

0 vs 5

3 vs 4

1 vs 3

- Many CSP Problems can be modelled by a multi-dimensional matrix of decision variables.

Round Robin Tournament Schedule

- Balanced Incomplete Block Design
- Set of Blocks (I)
- Set of objects in each block (I)

- Rack Configuration
- Set of cards (PI)
- Set of rack types
- Set of occurrences of each rack type (I)

- Social Golfers
- Set of rounds (I)
- Set of groups(I)
- Set of golfers(I)

- Steel Mill Slab Design
- Printing Template Design
- Warehouse Location
- Progressive Party Problem
- …

- a, b, c, d are indistinguishable values

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{b, d}

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Now the rows are indistinguishable

- Indistinguishable Rows

- 2 Dimensions
- [A B C] lex [D E F] lex [G H I]

- N Dimensions
- flatten([A B C]) lex
- flatten([D E F]) lex
- flatten([G H I])

Consistent

Consistent

Inconsistent

Inconsistent

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Swap 2 columns

Swap row 1 and 3

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- All variables take distinct values
- Push largest value to a particular corner, and
- Order the row and column containing that value

- 2 distinct values, one of which has at most one occurrence in each row or column.
- Lex order the rows and the columns

- Each row is a different multiset of values
- Multiset order the rows and lex order the columns

- We have developed a linear time algorithm for enforcing generalized arc-consistency on a lexicographic ordering constraint between two vectors of variables.
- Experiments show that in some cases it is vastly superior to previous consistency algorithms, both in time and in amount pruned.

- Not transitive
GAC(V1lexV2) and

GAC(V2lexV3) does not imply

GAC(V1lexV3)

- Not pair-wise decomposable

does not imply

GAC(V1lexV2 lex … lex Vn)

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ABCDEF is minimal among the index symmetries

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F

- ABCDEF ACBDFE
- ABCDEF BCAEFD
- ABCDEF BACEDF
- ABCDEF CABFDE
- ABCDEF CBAFED
- ABCDEF DFEACB

- ABCDEF EFDBCA
- ABCDEF EDFBAC
- ABCDEF FDECAB
- ABCDEF FEDCBA
- ABCDEF DEFABC

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Columns are lex ordered

1. BE CF

3. AD BE

1st row all permutations of 2nd

6. ABC DFE

8. ABC EDF

10. ABC FED

11. ABC DEF

9. ABC FDE

7. ABCD EFDB

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Swap 2 rows

Rotate columns left

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Both satisfy 7. ABC EFD

Right one satisfies 7. ABCD EFDB(1353 5133)

Left one violates 7. ABCD EFDB(1355 1353)

- Symmetry-Breaking Predicates for Search Problems
[J. Crawford, M. Ginsberg, E. Luks, A. Roy, KR ~97].

- Many problems have models using a multi-dimensional matrix of decision variables in which there is index symmetry.
- Constraint toolkits should provide facilities to support this.
- We have laid some foundations towards developing such facilities.
- Open problems remain.