Stable model semantics for founded bounds
Answer Set Programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable model semantics, which rule out solutions representing certain kinds of circular reasoning. Unfortunately, current ASP solvers are incapable of solving p...
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| Published in | Theory and practice of logic programming Vol. 13; no. 4-5; pp. 517 - 532 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Cambridge, UK
Cambridge University Press
01.07.2013
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1471-0684 1475-3081 |
| DOI | 10.1017/S147106841300032X |
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| Abstract | Answer Set Programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable model semantics, which rule out solutions representing certain kinds of circular reasoning. Unfortunately, current ASP solvers are incapable of solving problems involving cyclic dependencies between multiple integer or continuous quantities effectively. In this paper, we generalize the notion of stable models to bound founded variables with arbitrary domains, where bounds on such variables need to be justified by some rule in the program in order for the model to be stable. We show how to handle significantly more general rule forms where bound founded variables can act as head or body variables, and where head and body variables can be related via complex constraints subject to certain monotonicity requirements. We describe a new unfounded set detection algorithm which allows us to enforce this generalization of the stable model semantics. We also show how these unfounded sets can be explained in order to allow effective conflict-directed clause learning. The new solver merges the best features of CP, SAT and ASP solvers and allows new types of problems to be solved very efficiently. |
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| AbstractList | Answer Set Programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce
stable model semantics
, which rule out solutions representing certain kinds of circular reasoning. Unfortunately, current ASP solvers are incapable of solving problems involving cyclic dependencies between multiple integer or continuous quantities effectively. In this paper, we generalize the notion of stable models to
bound founded variables
with arbitrary domains, where
bounds
on such variables need to be justified by some rule in the program in order for the model to be stable. We show how to handle significantly more general rule forms where bound founded variables can act as head or body variables, and where head and body variables can be related via complex constraints subject to certain monotonicity requirements. We describe a new unfounded set detection algorithm which allows us to enforce this generalization of the stable model semantics. We also show how these unfounded sets can be explained in order to allow effective conflict-directed clause learning. The new solver merges the best features of CP, SAT and ASP solvers and allows new types of problems to be solved very efficiently. Abstract Answer Set Programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable model semantics, which rule out solutions representing certain kinds of circular reasoning. Unfortunately, current ASP solvers are incapable of solving problems involving cyclic dependencies between multiple integer or continuous quantities effectively. In this paper, we generalize the notion of stable models to bound founded variables with arbitrary domains, where bounds on such variables need to be justified by some rule in the program in order for the model to be stable. We show how to handle significantly more general rule forms where bound founded variables can act as head or body variables, and where head and body variables can be related via complex constraints subject to certain monotonicity requirements. We describe a new unfounded set detection algorithm which allows us to enforce this generalization of the stable model semantics. We also show how these unfounded sets can be explained in order to allow effective conflict-directed clause learning. The new solver merges the best features of CP, SAT and ASP solvers and allows new types of problems to be solved very efficiently. [PUBLICATION ABSTRACT] Answer Set Programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable model semantics, which rule out solutions representing certain kinds of circular reasoning. Unfortunately, current ASP solvers are incapable of solving problems involving cyclic dependencies between multiple integer or continuous quantities effectively. In this paper, we generalize the notion of stable models to bound founded variables with arbitrary domains, where bounds on such variables need to be justified by some rule in the program in order for the model to be stable. We show how to handle significantly more general rule forms where bound founded variables can act as head or body variables, and where head and body variables can be related via complex constraints subject to certain monotonicity requirements. We describe a new unfounded set detection algorithm which allows us to enforce this generalization of the stable model semantics. We also show how these unfounded sets can be explained in order to allow effective conflict-directed clause learning. The new solver merges the best features of CP, SAT and ASP solvers and allows new types of problems to be solved very efficiently. |
| Author | CHU, GEOFFREY STUCKEY, PETER J. AZIZ, REHAN ABDUL |
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| Copyright | Copyright © 2013 [REHAN ABDUL AZIZ, GEOFFREY CHU and PETER J. STUCKEY] |
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| References | Van Gelder (S147106841300032X_ref25) 1988 Rossi (S147106841300032X_ref22) 2006 Gebser (S147106841300032X_ref10) 2007 Osorio (S147106841300032X_ref21) 1996 Gebser (S147106841300032X_ref12) 2009 S147106841300032X_ref24 Anger (S147106841300032X_ref1) 2006 S147106841300032X_ref23 Liu (S147106841300032X_ref15) 2012 Nieuwenborgh (S147106841300032X_ref20) 2006 Aziz (S147106841300032X_ref2) 2013 Gebser (S147106841300032X_ref9) 2012 S147106841300032X_ref6 S147106841300032X_ref11 S147106841300032X_ref5 S147106841300032X_ref8 Moskewicz (S147106841300032X_ref18) 2001 S147106841300032X_ref7 S147106841300032X_ref17 S147106841300032X_ref16 S147106841300032X_ref3 Nethercote (S147106841300032X_ref19) 2007 Janssen (S147106841300032X_ref14) 2008 Baselice (S147106841300032X_ref4) 2005 Gelfond (S147106841300032X_ref13) 1988 |
| References_xml | – ident: S147106841300032X_ref5 doi: 10.1007/978-3-642-34922-5_15 – start-page: 359 volume-title: Proceedings of Logics in Artificial Intelligence, 10th European Conference, JELIA 2006 year: 2006 ident: S147106841300032X_ref20 – ident: S147106841300032X_ref8 – start-page: 386 volume-title: Proceedings of the 20th International Joint Conference on Artificial Intelligence year: 2007 ident: S147106841300032X_ref10 – start-page: 1070 volume-title: Proceedings of the Fifth International Conference on Logic Programming year: 1988 ident: S147106841300032X_ref13 – start-page: 530 volume-title: Proceedings of the 38th Design Automation Conference year: 2001 ident: S147106841300032X_ref18 – ident: S147106841300032X_ref7 doi: 10.1017/S1471068410000220 – start-page: 221 volume-title: Proceedings of the ACM Symposium on Principles of Database Systems year: 1988 ident: S147106841300032X_ref25 – start-page: 52 volume-title: Proceedings of the 21st International Conference on Logic Programming year: 2005 ident: S147106841300032X_ref4 – volume-title: Handbook of Constraint Programming (Foundations of Artificial Intelligence) year: 2006 ident: S147106841300032X_ref22 – ident: S147106841300032X_ref17 doi: 10.1007/s10472-009-9116-y – ident: S147106841300032X_ref3 doi: 10.1017/CBO9780511543357 – start-page: 58 volume-title: Proceedings of the International Workshop on Nonmonotonic Reasoning year: 2006 ident: S147106841300032X_ref1 – start-page: 32 volume-title: Proceedings of the 13th International Conference on Principles of Knowledge Representation and Reasoning year: 2012 ident: S147106841300032X_ref15 – volume-title: Answer Set Solving in Practice year: 2012 ident: S147106841300032X_ref9 doi: 10.2200/S00457ED1V01Y201211AIM019 – start-page: 71 volume-title: Proceedings of Non-Monotonic Extensions of Logic Programming, NMELP '96 year: 1996 ident: S147106841300032X_ref21 – ident: S147106841300032X_ref24 doi: 10.1016/S0004-3702(02)00187-X – ident: S147106841300032X_ref11 doi: 10.1016/j.artint.2012.04.001 – start-page: 529 volume-title: Proceedings of the 13th International Conference on the Principles and Practice of Constraint Programming year: 2007 ident: S147106841300032X_ref19 – start-page: 235 volume-title: Proceedings of the 25th International Conference on Logic Programming year: 2009 ident: S147106841300032X_ref12 – ident: S147106841300032X_ref6 – start-page: 362 volume-title: Proceedings of the 24th International Conference on Logic Programming year: 2008 ident: S147106841300032X_ref14 – ident: S147106841300032X_ref23 doi: 10.1145/1452044.1452046 – start-page: 41 volume-title: Proceedings of the Thirty-Sixth Australasian Computer Science Conference year: 2013 ident: S147106841300032X_ref2 – ident: S147106841300032X_ref16 doi: 10.1109/12.769433 |
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| Snippet | Answer Set Programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable model... Answer Set Programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable model... Abstract Answer Set Programming (ASP) is a powerful form of declarative programming used in areas such as planning or reasoning. ASP solvers enforce stable... |
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| SubjectTerms | Algorithms Declarative programming Domains Integer programming International conferences Logic programming Mathematical programming Reasoning Regular Papers Semantics Solvers Variables |
| Title | Stable model semantics for founded bounds |
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