CILC 2020 features three main keynotes and a Tutorial. Short info about the speakers are reported below.
Keynote Title: On the informal semantics of knowledge representation languages and the case of Logic Programming
Abstract: The informal semantics of a formal language aims to express the knowledge conveyed by formulas and theories of the language about the application domain, in a precise and systematic way. Viewing a (declarative) formal language as a tool to encode computational problems, the question of its informal semantics may not even be a scientific question. In this talk, we will view a formal KR language as a formal scientific model of certain types of knowledge. The question of its informal semantics then becomes the corner stone of such a scientific model, as it relates the formal entities (the formulas) to the informal objects that they intend to represent (the knowledge). The hope with this approach is to base discussions on this topic on more solid scientific ground. The lecture starts with a discussion on the feasabiliy of viewing a formal language as a formal scientific model of knowledge, and experimental methods to verify proposed informal semantics. These methods are applied to clarify the informal semantics of Logic Programming. Two main ideas for informal semantics of LP were proposed: logic programs as definitions, and the (auto)epistemic/default interpretation. We then analyze when these informal semantics apply, when they agree and disagree, what is the meaning of negation and the rule operator and which informal semantics applies in the context of concrete examples.
Marc Denecker obtained a master of mathematics and of computer science at the KU Leuven in Belgium. In 1993 he obtained his PhD at this university on Abductive Logic Programming, a topic that he explored later with respect to semantics, algorithms and knowledge representation. Together with Prof. Tony Kakas, his group developed the A-system that combined abduction with constraint programming. As a solution for the problem of the declarative nature of logic programming, he elaborated the declarative view of Logic Programming as a logic of inductive definitions, a theme in his research until today. In 2001, he became assistant professor at the Université Libre de Bruxelles. But one year later, he obtained a research position at the KU Leuven and returned to the KUL. Currently, he is head of the KRR research group (Knowledge Representation and Reasoning). A few persistent research themes are: formal and informal semantics of Knowledge Representation languages, Logic Programming and Non-monotonic languages. He continues to explore the relationship between Logic Programming and inductive definitions. He co-developed a fixpoint theory covering the main semantics of some important nonmonotonic formalisms. He proposed the logic FO(.) as a KR language integrating the classical logic and Logic Programming paradigms. He and his team developed the knowledge base system IDP for FO(.) based on techniques from SAT, Constraint Programming and Answer Set Programming (https://dtai.cs.kuleuven.be/software/idp). The group explores the Knowledge Base paradigm, where a knowledge base is reused to solve multiple sorts of problems using various forms of inferences. This has led to various small projects with industry to explore the use of knowledge-based technology. A current research theme in his group is the development of an interactive AI assistant for model search. He teaches courses on logic, modelling, knowledge representation, automata and computability and complexity theory.
Keynote Title: Reversibility of Actions and Plans
Abstract: In planning and reasoning about action and change, reversibility of actions is the problem of deciding whether the effects of an action can be reverted by applying other actions in order to return to the original state. This notion is sometimes also known as undoability. We analyze this and motivate that there are at least two alternative definitions for this notion. We also show complexity analyses and give an overview of existing tools.
Wolfgang Faber serves as Professor of Semantic Systems and Head of the Department of Applied Informatics at the University of Klagenfurt (Austria). Before that, he was a Professor at the University of Huddersfield (UK), an Associate Professor at the University of Calabria (Italy), and an Assistant Professor at the Vienna University of Technology (Austria), where he also obtained his PhD in 2002. From 2004 to 2006 he was on an APART grant of the Austrian Academy of Sciences. His general research interests are in knowledge representation, logic programming, nonmonotonic reasoning, planning, and knowledge-based agents. He has published more than 100 refereed articles in major journals, collections, and conference proceedings. He is one of the architects of DLV, a system for computing answer sets of disjunctive deductive databases, which is used all over the world. He has acted as a chair for several workshops and conferences, has been on the program committees of many of the major conferences of his research areas, and has served on the editorial board and as a reviewer for many journals and conferences on Artificial Intelligence, Knowledge Representation, and Logic Programming.
Keynote Title: Computational Argumentation — Formal Models and Complexity Results
Abstract: Argumentation is a communicative and international act aimed at resolving a difference of opinion. The last two decades have seen a formal and computational turn in argumentation theory with the goal to automate different aspects of argumentation. This leads to several challenges from an AI perspective, including efficient algorithms that need to be designed to guarantee short response times of argumentation systems. In this talk, I first give a broad overview on the area of computational argumentation and discuss shortcomings of current approaches. We then identify a particular leak in the popular argumentation-pipeline model, where conflict resolution is solely based on abstract arguments rather than on the arguments' claims. I will introduce a new formal model that shifts the focus from arguments to claims and give a comprehensive complexity analysis of several argumentation semantics under this claim-centric view. In addition, the talk addresses the complexity of sub-classes and presents novel parameterizations – which exploit the nature of claims explicitly – along with fixed-parameter tractability results.
Stefan Woltran is full professor of Foundations of Artificial Intelligence at Vienna University of Technology. His research focuses on problems in the area of knowledge representation and reasoning, argumentation, complexity analysis in AI and logic programming. In winter term 2013, he held a deputy professorship at Leipzig University. In 2013, he also received the prestigious START award from the Austrian Science Fund (FWF). He served as steering committee member for KR Inc., COMMA, and NMR and as co-organizer of international conferences including COMMA'12 and KR'14. He acted as PC Chair for the 10th International Symposium on Foundations of Information and Knowledge Systems (FoIKS'18) and for the 15th International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR'19). He has lead several research projects funded by FWF and Vienna Science and Technology Fund (WWTF). Since 2018 he is a fellow of the European Association for Artificial Intelligence.
Tutorial Title: Introduction to Probabilistic Ontologies
Abstract: Probabilities are a prominent formalism for measuring and handling uncertainty. It is thus natural to try to use them to represent uncertain knowledge in an ontology. However, building a probabilistic ontology requires many design choices, many of which are often made implicitly or without fully grasping their consequences. In this tutorial, we take a look at these design choices, what they mean, and when can they be used adequately.
Rafael Peñaloza serves as Associate Professor at the University of Milano-Bicocca, Italy. After obtaining his PhD (Dr. rer. nat.) from TU Dresden, Germany, he started working on formalisms for representing imperfect knowledge; specifically, on the properties of Fuzzy Description Logics (FDL), and later on probabilistic extensions of DLs. His main interest in this direction is the use of probabilities to model uncertainty in expert knowledge through probabilistic ontologies, and the way this uncertainty propagates to the conclusions derivable from them. Still he likes to consider different topics at the same time. He has over 100 publications in highly ranked international conferences and journals. He likes to read and write, and take long walks. He is also known for taking way too many pictures.