Invited Talks
Programme Co-Chairs
Tommie Meyer
Meraka Institute, Building 43, CSIR
Meiring Naude Avenue, Brummeria,
Pretoria,
South Africa
Phone: +27 12 841 4017
Fax: +27 12 841 4720
Eugenia Ternovska
School of Computing Science
Simon Fraser University
Burnaby, B.C.
Canada
Phone: +1 778.782.4771
Fax: +1 778.782.3045
Ray Reiter and Nonmonotonic Reasoning
by Jack Minker
Ray Reiter, was one of the leading researchers in the field of artificial intelligence at the time of his death, September 16, 2002, at the age of 63. He received many awards for his seminal contributions: Fellow of the ACM, the AAAI, the Royal Society of Canada and 1993 IJCAI Outstanding Contribution Award.
Ray was a principal founder of the field of nonmonotonic reasoning, generally considered to have started in 1980. Thirty years later, in 2010, in the city of his birth, Toronto, we appropriately celebrate Ray at the International Conference on Nonmonotonic Reasoning. In this talk, I discuss Ray, the person, his major contributions to artificial intelligence in data and knowledge bases, default reasoning, cognitive robotics, dynamic systems and other topics related to nonmonotonic reasoning. I also discuss work spawned by his contributions.
It is a tribute to Ray that his seminal research is still as vibrant and cited today as it was 30 years ago.
Arming Tweety with Jet Engines (is not enough)
by Torsten Schaub
Answer Set Programming (ASP) is nowadays regarded as the major computational offspring of Nonmonotonic Reasoning (NMR). Beginning in NMR with phenomenon-oriented studies of nonmonotonicity in commonsense reasoning in the eighties, ASP has evolved into an attractive declarative problem solving paradigm,combining a rich but simple modeling language with high-performance solving capacities. This development has also led to evolving problem scenarios, beginning with the famous Tweety scenarios, to artificial combinatorial problems, up to many case-studies as well as the first success stories in application domains. Despite its increasing popularity, however, ASP cannot yet be regarded as an
established technology, matching the needs for a widely used problem solving paradigm.
The talk will address this problem and discuss some of the major bottlenecks, challenges, and prospective solutions that ASP has to deal with in order to accomplish a true success story beyond the realm of Nonmonotonic Reasoning.
Dialectical Frameworks: Abstract Argumentation Beyond Dung
by Gerhard Brewka
We will present dialectical frameworks, a powerful generalization of Dung-style argumentation frameworks where each node comes with an associated acceptance condition. This allows us to model different types of dependencies, e.g. support and attack, as well as different types of nodes within a single framework. We show that Dung's standard semantics can be generalized to dialectical frameworks, in case of stable and preferred semantics to a slightly restricted class which we call bipolar frameworks.
We show how acceptance conditions can be conveniently represented using weights respectively priorities on the links. We also demonstrate how some of the proof standards known from legal reasoning can be modeled based on this idea.
Furthermore, we establish links between dialectical frameworks and existing argumentation systems like Carneades. We also establish relationships to logic programming.
On the informal and formal semantics of Default and Autoepistemic logic
by Marc Denecker
Default and Autoepistemic logic were devised to model similar kinds of common sense reasoning patterns. The talk revisits the intuitions of Reiter and Moore in the context of the unifying semantic framework developed by Denecker, Marek and Truszczynski.
Axiom Pinpointing in Description Logics
by Franz Baader
Description Logics (DL) are a successful family of logic-based knowledge representation languages, which can be used to represent the conceptual knowledge of an application domain in a structured and formally well-understood way. They are employed in various application domains, such as natural language processing, databases, the semantic web, and biomedical ontologies. As the size of DL knowledge
bases (KBs) grows, tools that support improving their quality become more important. Standard DL reasoning can be used to computed implicit consequences such as inconsistencies and inferred subsumption relationships, but it does not explain the reasons for a given consequence.
Axiom pinpointing is a first step towards providing such an explanation. Given a DL knowledge base and a consequence, it computes minimal subsets of the axioms of the KB that have the consequence (MinAs).
In the talk, I will give an overview over different approaches for computing MinAs employed in the DL community, and also mention results on the complexity of the problem of computing all MinAs and of related
decision problems.