Belief Revision and Non-Monotonic Reasoning

Belief revision is the process of changing one’s belief state when a newly acquired information contradicts one’s beliefs. Belief revision has been a widely studied topic in the areas of artificial intelligence (AI). However, how exactly humans perform belief revision is still an unresolved terrain. Non-monotonic reasoning is a form of thinking in which additional information requires the withdrawal of prior beliefs and thus leads to less reliable knowledge. The research in both fields is essential for the attempt to understand human reasoning in an uncertain world and the question how people deal with non-monotonic and defeasible inferences. Human reasoners, for instance, perform changes of their minds in the light of contradicting evidence and integrate conflicting information into existing belief sets. Work in these areas is also important in artificial intelligence research and the development of functioning data bases. Much work has been done by psychologists, computer scientists, and philosophers in the recent years. The approaches, however, often remain restricted to one discipline.

The workshop brings together leading researchers with different disciplinary backgrounds to discuss various concepts of belief revision and non-monotonicity. Experts from philosophy, computer science, and psychology will talk about belief revision and non-monotonic reasoning from the perspective of their disciplines with the clear intention to provide knowledge for an interdisciplinary audience. Planned are intensive sessions, targeting to elaborate current topics across disciplinary borders. The participants will work on the identification of links between the disciplines that allow to act in concert within the often heterogeneous fields.