Preferred Answer Sets for Ordered Logic Programs

Nieuwenborgh, Davy Van; Vermeir, Dirk

doi:10.1007/3-540-45757-7_36

Cited by 28 publications

(32 citation statements)

References 7 publications

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“…These are used to select the most preferred stable models. [29] also proposes a formalism that uses the order among rules to induce an order on answer sets for inconsistent programs, making it unclear on how to represent decisions. Along the same line, [18] proposes logic programs with compiled preferences, where preferences may appear in any part of the rules.…”

Section: Relationship To Other Approachesmentioning

confidence: 99%

Implementing Ordered Choice Logic Programming Using Answer Set Solvers

Vos

2004

Lecture Notes in Computer Science

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Abstract. Ordered Choice Logic Programming (OCLP) allows for dynamic preference-based decision-making with multiple alternatives without the need for any form of negation. This complete absence of negation does not weaken the language as both forms (classical and as-failure) can be intuitively simulated in the language and eliminated using a simple pre-processor, making it also an easy language for users less familiar with logic programming. The semantics of the language is based on the preference between alternatives, yielding both a skeptical and a credulous approach. In this paper we demonstrate how OCLPs can be translated to semi-negative logic programs such that, depending on the transformation, the answer sets of the latter correspond with the skeptical/credulous answer sets of the former. By providing such a mapping, we have a mechanism for implementing OCLP using answer set solvers like Smodels or dlv. We end with a discussion of the complexity of our system and the reasoning tasks it can perform.

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Section: Relationship To Other Approachesmentioning

confidence: 99%

Implementing Ordered Choice Logic Programming Using Answer Set Solvers

Vos

2004

Lecture Notes in Computer Science

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“…We give some preliminaries concerning the extended answer set semantics [22]. A literal is an atom a or a negated atom ¬a.…”

Section: Agent Hierarchiesmentioning

confidence: 99%

“…From Theorem 4 in [22] we have that the extended answer sets of P are exactly the answer sets of E(P ). We can then rewrite a weak agent as a rule agent by introducing for each weak constraint w : ← β rules w ← β and ¬w ← β such that w is in an answer set if the constraint is violated.…”

Section: Relationship With Weak Constraintsmentioning

confidence: 99%

“…We can identify two directions for these preferences relations on programs. On the one hand, we can equip a logic program with a preference relation on the rules [18, 17, 15,10,7,5,27,1,22], while on the other hand we can consider a preference relation on the (extended) literals in the program: [21] proposes explicit preferences while [4,6] encodes dynamic preferences within the program.…”

Section: Introductionmentioning

confidence: 99%

“…a route planner agent may contain inconsistent information regarding some particular regions in Europe, which should not stop it from providing travel directions in general. The extended answer set semantics from [22,23] allows for the defeat of problematic rules. Take, for example, the program consisting of a ← b, b ← and ¬a ← .…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical Decision Making by Autonomous Agents

Heymans

Nieuwenborgh

Vermeir

2004

Logics in Artificial Intelligence

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Abstract. Often, decision making involves autonomous agents that are structured in a complex hierarchy, representing e.g. authority. Typically the agents share the same body of knowledge, but each may have its own, possibly conflicting, preferences on the available information. We model the common knowledge base for such preference agents as a logic program under the extended answer set semantics, thus allowing for the defeat of rules to resolve conflicts. An agent can express its preferences on certain aspects of this information using a partial order relation on either literals or rules. Placing such agents in a hierarchy according to their position in the decision making process results in a system where agents cooperate to find solutions that are jointly preferred. We show that a hierarchy of agents with either preferences on rules or on literals can be transformed into an equivalent system with just one type of preferences. Regarding the expressiveness, the formalism essentially covers the polynomial hierarchy. E.g. the membership problem for a hierarchy of depth n is Σ P n+2 -complete. We illustrate an application of the approach by showing how it can easily express a generalization of weak constraints, i.e. "desirable" constraints that do not need to be satisfied but where one tries to minimize their violation.

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Consistent Query Answering

Chomicki

Integrity and Internal Control in Information Systems VI

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Preferred Answer Sets for Ordered Logic Programs

Cited by 28 publications

References 7 publications

Implementing Ordered Choice Logic Programming Using Answer Set Solvers

Implementing Ordered Choice Logic Programming Using Answer Set Solvers

Hierarchical Decision Making by Autonomous Agents

Consistent Query Answering

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