74 research outputs found
A Program-Level Approach to Revising Logic Programs under the Answer Set Semantics
An approach to the revision of logic programs under the answer set semantics
is presented. For programs P and Q, the goal is to determine the answer sets
that correspond to the revision of P by Q, denoted P * Q. A fundamental
principle of classical (AGM) revision, and the one that guides the approach
here, is the success postulate. In AGM revision, this stipulates that A is in K
* A. By analogy with the success postulate, for programs P and Q, this means
that the answer sets of Q will in some sense be contained in those of P * Q.
The essential idea is that for P * Q, a three-valued answer set for Q,
consisting of positive and negative literals, is first determined. The positive
literals constitute a regular answer set, while the negated literals make up a
minimal set of naf literals required to produce the answer set from Q. These
literals are propagated to the program P, along with those rules of Q that are
not decided by these literals. The approach differs from work in update logic
programs in two main respects. First, we ensure that the revising logic program
has higher priority, and so we satisfy the success postulate; second, for the
preference implicit in a revision P * Q, the program Q as a whole takes
precedence over P, unlike update logic programs, since answer sets of Q are
propagated to P. We show that a core group of the AGM postulates are satisfied,
as are the postulates that have been proposed for update logic programs
Logic Programs with Compiled Preferences
We describe an approach for compiling preferences into logic programs under
the answer set semantics. An ordered logic program is an extended logic program
in which rules are named by unique terms, and in which preferences among rules
are given by a set of dedicated atoms. An ordered logic program is transformed
into a second, regular, extended logic program wherein the preferences are
respected, in that the answer sets obtained in the transformed theory
correspond with the preferred answer sets of the original theory. Our approach
allows both the specification of static orderings (as found in most previous
work), in which preferences are external to a logic program, as well as
orderings on sets of rules. In large part then, we are interested in describing
a general methodology for uniformly incorporating preference information in a
logic program. Since the result of our translation is an extended logic
program, we can make use of existing implementations, such as dlv and smodels.
To this end, we have developed a compiler, available on the web, as a front-end
for these programming systems
Current and Future Challenges in Knowledge Representation and Reasoning
Knowledge Representation and Reasoning is a central, longstanding, and active
area of Artificial Intelligence. Over the years it has evolved significantly;
more recently it has been challenged and complemented by research in areas such
as machine learning and reasoning under uncertainty. In July 2022 a Dagstuhl
Perspectives workshop was held on Knowledge Representation and Reasoning. The
goal of the workshop was to describe the state of the art in the field,
including its relation with other areas, its shortcomings and strengths,
together with recommendations for future progress. We developed this manifesto
based on the presentations, panels, working groups, and discussions that took
place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge
Representation: its origins, goals, milestones, and current foci; its relation
to other disciplines, especially to Artificial Intelligence; and on its
challenges, along with key priorities for the next decade
Conservative Belief Change
A standard assumption underlying traditional accounts of belief change is the principle of minimal change, that an agent's belief state should be modified minimally to incorporate new information. In this paper we introduce a novel account of belief change in which the agent's belief state is modified minimally to incorporate exactly the new information. Thus a revision by p#q will result in a new belief state in which p#q is believed, but a stronger proposition (such as p q) is not, regardless of the initial form of the belief state. This form of belief change is termed conservative belief change and corresponds to a Gricean interpretation of the input formula. We investigate belief revision in this framework, and provide a representation result between a set of postulates characterising this form of belief change and a construction in terms of systems of spheres. This approach is extended to that of belief revision with respect to a specified context. Last, we show how this approach resolves a longstanding problem in belief revision
On a Rule-Based Interpretation of Default Conditionals
In nonmonotonic reasoning, a default conditional α → β has most often been informally interpreted as a defeasible version of a classical conditional, usually the material conditional. There is however an alternative interpretation, in which a default is regarded essentially as a rule, leading from premises to conclusion. In this paper, we present a family of logics, based on this alternative interpretation. A general semantic framework under this rule-based interpretation is developed, and associated proof theories for a family of weak conditional logics is specified. Nonmonotonic inference is easily defined in these logics. Interestingly, the logics presented here are weaker than the commonly-accepted base conditional approach for defeasible reasoning. However, this approach resolves problems that have been associated with previous approaches.
Towards a Rule-Based Interpretation of Conditional Defaults
For nonmonotonic reasoning, a default conditional # has most often been informally interpreted as a defeasible version of a classical conditional, usually the material conditional. There is howeve
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