Content: First Workshop

First Workshop

The First Hybris Workshop will take place on November 15th-16th in at the RWTH Aachen University, Aachen, Germany.


Wednesday, November 14

Travel to Aachen

Thursday, November 15

09:00-10:00Invited Talk by Thomas Eiter, TU Wien
Paraconsistent Modular Answer Set Programming (Abstract)
10:00-10:30Coffee Break
10:30-13:00Talks by project partners
A1Martin Liebenberg, RWTH Aachen
Towards Decidable Verification of Non-Terminating Golog Programs
Benjamin Zarriess, TU Dresden
On the Verification Problem of Regular Description Logic Action Programs
A2Stefan Ellmauthaler, Uni Leipzig
Abstract Dialectical Frameworks
Philipp Obermeier, Uni Potsdam
Stream Reasoning with Reactive Answer Set Programming
B1Max Ostrowski, Uni Potsdam
Constraint Answer Set Programming for Biological Applications
14:00-16:00Talks by project partners
B2George Tsatsaronis, TU Dresden
Entity Extraction and Ontology Generation
Yue Ma, TU Dresden
Generating logical definitions for biomedical concepts from texts: preliminary results
C1Andreas Hertle, Uni Freiburg
Planning with Semantic Attachments: An Object-Oriented View
Nichola Abdo, Uni Freiburg
From Low-Level Trajectory Demonstrations to Symbolic Actions for Planning
16:00-16:30Coffee Break
16:30-18:30PIs: Internal Hybris Meeting
Others: discussions among participants
20:00Dinner for PI's and Invited Speakers

Friday, November 16

09:00-10:00Invited Talk by Gabriele Kern-Isberner, TU Dortmund
Structures for Uncertain and Dynamic Reasoning (Abstract)
10:00-10:30Coffee Break
10:30-12:30Tutorial by Torsten Schaub, Uni Potsdam
Answer Set Programming Tutorial
(Teaching Material)
12:30-14:00Lunch and Farewell


Paraconsistent Modular Answer Set Programming

Invited Talk by Thomas Eiter, TU Wien

Abstract: Paraconsistent reasoning is a well-studied approach to deal with inconsistency in logical theories in a way such that inference does not explode. It has specifically been considered in the area of knowledge representation and reasoning for a range of different formalisms, including also non-monotonic formalisms such as logic programming. In the last years, there has been increasing interest in datalog-based formalisms, including traditional Answer Set Programming, and extensions of the formalisms to encompass modularity have been conceived. In this talk, we shall address the issue of paraconsistency for modular logic programs in a datalog setting, under the answer set semantics for logic programs. The two orthogonal aspects of modularity and paraconsistency may be approached on different grounds. Recent work at TU Wien on these aspects lends for a combination in a single formalism, which still leaves issues and challenges for ongoing research, regarding semantics and evaluation, both in theory and for practical concerns. (Joint work with Minh Dao-Tran, Michael Fink, Thomas Krennwallner)

Structures for Uncertain and Dynamic Reasoning

Invited Talk by Invited Talk by Gabriele Kern-Isberner, TU Dortmund

Abstract: From the idea of giving up monotonicity in logic-based reasoning to comply better with the requirements of everyday life, a plethora of methods have emerged. On the one hand, from the classical logical side, default logics aim at taking the possibility of exceptions explicitly into account, or at loosening the strict link between antecedent and consequent in logical rules. One the other hand, from the probabilistic side, quantitative information was based on qualitative, logic-like structures. In between, semi-quantitative approaches like ranking functions (alternatively, possibilistic theory) and Dempster-Shafer's evidence theory were proposed to (hopefully) bridge the gap between symbolic and fully quantitative theories. Moreover, belief revision theory came into being as "the other side of uncertain reasoning", aiming at catching epistemic changes when new information arrives.

All these approaches reflect different facets of rational commonsense reasoning and come along with different technical peculiarities which go beyond classical logic. In this talk it is shown how conditionals as carriers of nonmonotonic, defeasible information may help to find reliable guidelines for uncertain reasoning in various semantical frameworks such as, e.g., ranking functions and probability theory. The algebraic theory of conditional structures provides a formal approach to measure interactions between conditionals, and to process conditional information in the respective semantics while observing these interactions. For instance, for the probabilistic domain, the application of these ideas leads to reasoning on maximum entropy. Moreover, the approach proves to be very helpful to address recently raised problems such as first-order default and probabilistic reasoning, and multiple epistemic revision.