Foundations, Applications & Theory of Inductive Logic (FAT IL)

Breadcrumb Navigation


Interdisciplinarity of Inductive Logic

Idea & Motivation

There is renewed interest in inductive logic in a number of separate fields. However, the lack of interaction across disciplines prevents the spread of ideas, which significantly reduces the impact of current work on inductive logic. This workshop is hence devoted to the interdisciplinarity of inductive logic, and we shall address such questions as: What are the ramifications of the success of machine learning vis-à-vis the wide-spread scepticism at the foundational level to justified successful inductive inference? How can the recent technical advances in inductive logic in uncertain inference and knowledge representation lead to novel applications and improved decision making? How does inductive logic make sense of Big Data?

The focus of the workshop is on the current work of network members. Particular interest will be paid to problems to which input from network members in other research traditions/areas will be most helpful, and to how their contributions will advance the respective fields. Exchange of ideas is further facilitated by extended feedback and Q&A periods after every talk, as well as brainstorming sessions that are intended to initiate new collaborations within the network and prepare the ground for joint projects.



Wednesday, 26 February

09:45 - 10:00 Introduction and welcome by Jürgen Landes
10:00 - 10:45 Jon Williamson: “Bayesianism, direct inference and the logic of induction”
10:45 - 11:30 Gabriele Kern-Isberner: “Inductive reasoning and belief revision”
11:30 - 12:15 Marta Sznajder: “The prehistory of inductive logic”
12:15 - 14:00 Lunch Break
14:00 - 14:45 Jürgen Landes: “MaxEnt and the requirement to update on ALL the available evidence”
14:45 - 15:30 Alena Vencovská: "A thrice justified principle of pure inductive logic"
15:30 - 16:00 Break
16:00 - 16:45 Matthias Thimm: “Computational approaches to reasoning with uncertain and inconsistent information”

Thursday, 27 February

09:30 - 10:15 Paul Thorn: Direct inference and inductive logic
10:15 - 11:00 Michał Godziszewski: "Elimination counterexamples and the Brier scoring rule"
11:00 - 11:45 Francesca Zaffora Blando: “Algorithmic randomness and Bayesian merging of opinion”
11:45 - 14:00 Lunch Break
14:00 - 17:00 Break-Out Sessions

Friday, 28 February

09:30 - 10:15 Dominik Klein: "Four-valued probabilities"
10:15 - 11:00 Martin Adamčík: “Meta-analysis: Dealing with both complex knowledge and unexplained heterogeneity in medical research”
11:00 - 11:45 Tom Sterkenburg: “The problem of induction and the success of machine learning”
12:00 - 13:00 Roundtable Diskussion