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

Idea & Motivation

The first conference of the network will have a focus on applications of inductive logic in computer science in general, and artificial intelligence in particular. In the latter, subareas such as commonsense reasoning, probabilistic reasoning, non-monotonic reasoning, automated planning, machine learning, and reasoning in the semantic web all require decision-making under uncertainty. This conference will invite researchers working in these areas in order to both inspire the network members with motivating scenarios and to bring the foundational knowledge of the network members to these application scenarios.

Questions we shall address are:

  • How should one select an inductive bias in practise?
  • What are the foundational limitations of artificial intelligence/machine learning from an inductive logic perspective?
  • How to cope with conflicting information?

Organizer

Keynote Speakers

Dov M. Gabbay (University of Luxembourg, Luxembourg)
Simon Hutteger (University of California, USA)
Ute Schmid (University of Bamberg, Germany)
Luc De Raedt (KU Leuven, Belgium)
Claudia D'Amato (Università degli Studi di Bari, Italy)

More information, including the call for papers, are available on the conference website: http://fatil2020.krportal.org/index.html

Registration

Reduced fee (for graduate students): 50 EUR
Regular fee: 80 EUR
Members of the MCMP and LMU: participation free of charge

The conference dinner is not included.

Please register via XING Events: