On the complexity of propositional knowledge base revision, updates, and counterfactuals
Artificial Intelligence
On the semantics of theory change: arbitration between old and new information
PODS '93 Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Theoretical Computer Science - Special issue: database theory
Strongly equivalent logic programs
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Complexity and expressive power of logic programming
ACM Computing Surveys (CSUR)
Extending and implementing the stable model semantics
Artificial Intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
Possibilistic Merging and Distance-Based Fusion of Propositional Information
Annals of Mathematics and Artificial Intelligence
Combining Multiple Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
Arbitration (or How to Merge Knowledge Bases)
IEEE Transactions on Knowledge and Data Engineering
Enhancing Disjunctive Datalog by Constraints
IEEE Transactions on Knowledge and Data Engineering
Multiagent Compromises, Joint Fixpoints, and Stable Models
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part I
Revision of Non-Monotonic Theories
JELIA '94 Proceedings of the European Workshop on Logics in Artificial Intelligence
An abductive framework for computing knowledge base updates
Theory and Practice of Logic Programming
Computing preferred answer sets by meta-interpretation in Answer Set Programming
Theory and Practice of Logic Programming
Strong equivalence made easy: nested expressions and weight constraints
Theory and Practice of Logic Programming
A framework for compiling preferences in logic programs
Theory and Practice of Logic Programming
On properties of update sequences based on causal rejection
Theory and Practice of Logic Programming
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Updates in answer set programming: An approach based on basic structural properties
Theory and Practice of Logic Programming
Propositional theories are strongly equivalent to logic programs
Theory and Practice of Logic Programming
Coordination in answer set programming
ACM Transactions on Computational Logic (TOCL)
Semantic forgetting in answer set programming
Artificial Intelligence
Merging Logic Programs under Answer Set Semantics
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
A meta-programming technique for debugging answer-set programs
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Towards generalized rule-based updates
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Abductive framework for nonmonotonic theory change
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
On solution correspondences in answer-set programming
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Solving logic program conflict through strong and weak forgettings
Artificial Intelligence
A preference-based framework for updating logic programs
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Constructing consensus logic programs
LOPSTR'06 Proceedings of the 16th international conference on Logic-based program synthesis and transformation
On Semantic Update Operators for Answer-Set Programs
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Combining answer sets of nonmonotonic logic programs
CLIMA'05 Proceedings of the 6th international conference on Computational Logic in Multi-Agent Systems
Belief revision within fragments of propositional logic
Journal of Computer and System Sciences
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We address the problem of belief change in (nonmonotonic) logic programming under answer set semantics. Our formal techniques are analogous to those of distance-based belief revision in propositional logic. In particular, we build upon the model theory of logic programs furnished by SE interpretations, where an SE interpretation is a model of a logic program in the same way that a classical interpretation is a model of a propositional formula. Hence we extend techniques from the area of belief revision based on distance between models to belief change in logic programs. We first consider belief revision: for logic programs P and Q, the goal is to determine a program R that corresponds to the revision of P by Q, denoted P * Q. We investigate several operators, including (logic program) expansion and two revision operators based on the distance between the SE models of logic programs. It proves to be the case that expansion is an interesting operator in its own right, unlike in classical belief revision where it is relatively uninteresting. Expansion and revision are shown to satisfy a suite of interesting properties; in particular, our revision operators satisfy all or nearly all of the AGM postulates for revision. We next consider approaches for merging a set of logic programs, P1, ..., Pn. Again, our formal techniques are based on notions of relative distance between the SE models of the logic programs. Two approaches are examined. The first informally selects for each program Pi those models of Pi that vary the least from models of the other programs. The second approach informally selects those models of a program P0 that are closest to the models of programs P1, ..., Pn. In this case, P0 can be thought of as a set of database integrity constraints. We examine these operators with regards to how they satisfy relevant postulate sets. Last, we present encodings for computing the revision as well as the merging of logic programs within the same logic programming framework. This gives rise to a direct implementation of our approach in terms of off-the-shelf answer set solvers. These encodings also reflect the fact that our change operators do not increase the complexity of the base formalism.