Beschreibung
Information for real life AI applications is usually pervaded by uncertainty and subject to change, and thus demands for non-classical reasoning approaches. At the same time, psychological findings indicate that human reasoning cannot be completely described by classical logical systems. Sources of explanations are incomplete knowledge, incorrect beliefs, or inconsistencies. A wide range of reasoning mechanism has to be considered, such as analogical or defeasible reasoning. The field of knowledge representation and reasoning offers a rich palette of methods for uncertain reasoning both to describe human reasoning and to model AI approaches.
Programm
09:00 - 10:00 Invited Talk
- Constructing, Weighing and Evaluating Arguments to Solve Wicked Problems
Tom Gordon
10:00 - 10:30 Session 1
- Ontology-Mediated Query Answering for Probabilistic Temporal Data with EL Ontologies
Patrick Koopmann
10:30 -11:00 Coffee
11:00 - 12:30 Session 2
- Explorations into Belief State Compression
Ali Elhalawaty and Haythem Ismail - Probabilistic Belief Update via Mixing Endogenous Actions and Exogenous Events
Gavin Rens and Thomas Meyer - Towards a Unified Algebraic Framework for Non-Monotonicity
Nourhan Ehab and Haythem Ismail
12:30 -14:00 Lunch
14:00 - 15:00 Invited Talk
- Inductive Programming as Approach to Comprehensible Machine Learning
Ute Schmid
15:00 - 15:30 Session 3
- Analyzing Knowledge Dynamics and its Implications on Intelligent Agents
Ingo J. Timm and Lukas Reuter
15:30 -16:00 Coffee
After the workshop:
16:00 - 16:30 Mitgliederversammlung der GI-Fachgruppe Wissensrepräsentation und Schließen