Dagstuhl Seminar Proceedings, Volume 5171
Dagstuhl Seminar Proceedings
DagSemProc
https://www.dagstuhl.de/dagpub/1862-4405
https://dblp.org/db/series/dagstuhl
1862-4405
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
5171
2005
https://drops.dagstuhl.de/entities/volume/DagSemProc-volume-5171
05171 Abstracts Collection – Nonmonotonic Reasoning, Answer Set Programming and Constraints
From 24.04.05 to 29.04.05, the Dagstuhl Seminar
05171 ``Nonmonotonic Reasoning, Answer Set Programming and Constraints''
was held in the International Conference and Research Center (IBFI),
Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available.
Knowledge representation
nonmonotonic reasoning
logic programming
answer-set programming
constraints
1-23
Regular Paper
Gerhard
Brewka
Gerhard Brewka
Ilkka
Niemelä
Ilkka Niemelä
Torsten
Schaub
Torsten Schaub
Miroslaw
Truszczynski
Miroslaw Truszczynski
Joost
Vennekens
Joost Vennekens
10.4230/DagSemProc.05171.1
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05171 Executive Summary – Nonmonotonic Reasoning, Answer Set Programming and Constraints
We provide a brief overview of the seminar and comment on most important research themes that emerged.
Knowledge representation
nonmonotonic reasoning
logic programming
answer-set programming
constraints
1-2
Regular Paper
Gerhard
Brewka
Gerhard Brewka
Ilkka
Niemelä
Ilkka Niemelä
Torsten
Schaub
Torsten Schaub
Miroslaw
Truszczynski
Miroslaw Truszczynski
10.4230/DagSemProc.05171.2
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Answer Set Programming and Combinatorial Voting
We show how Logic Programming with Ordered
Disjunction (LPOD), the extension of answer
set programming for handling preferences, may
be used for representing and solving collective
decision making problems. We present the
notion of combinatorial vote problem in the
context of LPOD and define various types of
vote rules, used as decision criteria for
determining optimal candidate for a group of voters.
15 min presentation
Decision making
answer set programming
preferences
1-15
Regular Paper
Rafal
Grabos
Rafal Grabos
10.4230/DagSemProc.05171.3
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Modelling and Implementing a Knowledge Base for Checking Medical Invoices with DLV
Checking medical invoices, done by every health insurance company,
is a labor-intensive task. Both speed and quality of executing
this task may be increased by the knowledge-based
decision support system ACMI which we present
in this paper.
As the relevant regulations also contain various default rules,
ACMI`s knowledge core is modelled
using the answer set programming paradigm. It turned out
that all relevant rules could be expressed directly in this framework,
providing for a declarative and easily extendable and
modifiable knowledge base.
ACMI is implemented using the DLV system.
Answer sets
default rules
health insurance
rule schemas
1-12
Regular Paper
Gabriele
Kern-Isberner
Gabriele Kern-Isberner
Christoph
Beierle
Christoph Beierle
Oliver
Dusso
Oliver Dusso
10.4230/DagSemProc.05171.4
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Normal Form Theorem for Logic Programs with Cardinality Constraints
We discuss proof schemes, a kind of context-dependent proofs for logic
programs. We show usefullness of these constructs both in the context of
normal logic programs and their generalizations due to Niemela and
collaborators. As an application we show the following result. For every
cardinality-constraint logic program P there is a logic program PÃ‚Â´ with the
same heads, but with bodies consisting of atoms and negated atoms such
that P and PÃ‚Â´ have same stable models. It is worth noting that another
proof of same result can be obtained from the results by Lifschitz and
collaborators.
Proof scheme
cardinality constraints
1-34
Regular Paper
Victor W.
Marek
Victor W. Marek
Jeffrey B.
Remmel
Jeffrey B. Remmel
10.4230/DagSemProc.05171.5
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Possibilistic Stable Models
We present the main lines of a new framework that we have defined in order to improve the knowledge representation power of Answer Set Programming paradigm.
Our proposal is to use notions from possibility theory to extend the stable model semantics by taking into account a certainty level, expressed in terms of necessity measure, on each rule of a normal logic program.
First of all, we introduce possibilistic definite logic programs and show how to compute the conclusions of such programs both in syntactic and semantic ways. The syntactic handling is done by help of a fix-point operator, the semantic part relies on a possibility distribution on all sets of atoms and the two approaches are shown to be equivalent.
In a second part, we define what is a possibilistic stable model for a normal logic program, with default negation. Again, we define a possibility distribution allowing to determine the stable models.
We end our presentation by showing how we can use our framework to adressing inconsistency in Answer Set Programming.
Non monotonic reasoning
uncertainty
possibility theory
1-6
Regular Paper
Pascal
Nicolas
Pascal Nicolas
Laurent
Garcia
Laurent Garcia
Igor
Stéphan
Igor Stéphan
10.4230/DagSemProc.05171.6
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Semantic Web Languages and Semantic Web Services as Application Areas for Answer Set Programming
In the Semantic Web and Semantic Web Services areas there are still unclear issues concerning an appropriate language. Answer Set Programming and ASP engines can be particularly interesting for Ontological Reasoning, especially in the light of ongoing discussions of non-Monotonic extensions for Ontology Languages. Previously, the main concern of discussions was around OWL and Description Logics. Recently many extensions and suggestions for Rule Languages and Semantic Web Languages pop up, particularly in the the context of Semantic Web Services, which involve the meta-data description of Services instaead of static data on the Web only. These lanuages involve SWRL, WSML, SWSL-Rules, etc. I want to give an outline of languages, challenges and initiatives in this area and where I think Answer Set Programming research can hook in. (30min).
Semantic Web
Semantic Web Services
Rule Lagnuages
RDF
RDFS
OWL
WSMO
WSML
OWL-S
SWSL
SWSF
1-6
Regular Paper
Axel
Polleres
Axel Polleres
10.4230/DagSemProc.05171.7
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Set Based Logic Programming
We propose a set of desiderata for extensions of Answer Set Programming to capture domains where the objects of interest are infinite sets and yet we can still process ASP programs effectively. We propose two different schemes to do this. One is to extend cardinality type constraints to set constraints which involve codes for finite, recursive and recursively enumerable sets. A second scheme to modify logic programming to reason about sets directly. In this setting, we can also augment logic programming with certain
monotone inductive operators so that we can reason about families of sets which have structure such a closed sets of a topological space or
subspaces of a vector space. We observe that under such conditions, the classic Gelfond-Lifschitz construction generalizes to at least two different notions of stable models.
ASP
codes for infinite sets
stable model generalizations
1-26
Regular Paper
Jeffrey B.
Remmel
Jeffrey B. Remmel
Victor W.
Marek
Victor W. Marek
10.4230/DagSemProc.05171.8
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