A
Alan M. Frisch
Researcher at University of York
Publications - 77
Citations - 2276
Alan M. Frisch is an academic researcher from University of York. The author has contributed to research in topics: Constraint (information theory) & Constraint satisfaction. The author has an hindex of 27, co-authored 76 publications receiving 2212 citations. Previous affiliations of Alan M. Frisch include Motorola & University of Rochester.
Papers
More filters
Proceedings Article
The design of ESSENCE: a constraint language for specifying combinatorial problems
TL;DR: Essence is a formal language for specifying combinatorial problems in a manner similar to natural rigorous specifications that use a mixture of natural language and discrete mathematics.
Journal Article
Breaking row and column symmetries in matrix models
Pierre Flener,Alan M. Frisch,Brahim Hnich,Zeynep Kiziltan,Ian Miguel,Justin Pearson,Toby Walsh +6 more
TL;DR: This work identifies an important class of symmetries in constraint programming, arising from matrices of decision variables where rows and columns can be swapped, and identifies special cases where all compositions of the row and column asymmetries can be eliminated by the addition of only a linear number of symmetry-breaking constraints.
Book ChapterDOI
Breaking Row and Column Symmetries in Matrix Models
Pierre Flener,Alan M. Frisch,Brahim Hnich,Zeynep Kiziltan,Ian Miguel,Justin Pearson,Toby Walsh +6 more
TL;DR: In this paper, the authors identify an important class of symmetries in constraint programming, arising from matrices of decision variables where rows and columns can be swapped, and they identify special cases where all compositions of the row and column symmetry can be eliminated by the addition of only a linear number of symmetry-breaking constraints.
Journal ArticleDOI
Essence: A constraint language for specifying combinatorial problems
Alan M. Frisch,Warwick Harvey,Christopher Jefferson,Bernadette Martínez-Hernández,Ian Miguel +4 more
TL;DR: Essence as discussed by the authors is a formal language for specifying combinatorial problems in a manner similar to natural rigorous specifications that use a mixture of natural language and discrete mathematics, providing a high level of abstraction.
Journal ArticleDOI
Anytime deduction for probabilistic logic
Alan M. Frisch,Peter Haddawy +1 more
TL;DR: The deduction method presented here contrasts with other methods whose ability to perform logical reasoning is either limited or requires finding all truth assignments consistent with the given sentences.