*Apologies for multiple postings.*
*Call for Papers*
1st International Joint Conference on Learning & Reasoning (IJCLR 2020),
Sept. 9-11 2020,
Athens, Greece.
http://lr2020.iit.demokritos.gr/
Integrating learning from experience with reasoning with what has been
learnt is one the key open questions in AI. It holds the potential of
addressing many of the shortcomings of contemporary AI approaches,
including the black-box nature and the brittleness of deep learning, and
the difficulty to adapt knowledge representation models in the light of
new data.
IJCLR 2020 brings together, for the first time, four international
conferences & workshops, addressing all aspects of combining knowledge
representation & machine reasoning with statistical, neural and symbolic
learning:
- The 30th International Conference on Inductive Logic Programming (ILP).
- The 15th International Workshop on Neural-Symbolic Learning &
Reasoning (NeSy).
- The 10th International Workshop on Statistical Relational Artificial
Inteligence (StarAI).
- The 10th International Workshop on Approaches and Applications of
Inductive Programming (AAIP).
The purpose of IJCLR 2020 is the presentation of cutting-edge research
on these fields, but also, to promote collaboration and
cross-fertilization between different approaches and methodologies to
integrating learning & reasoning, via joint discussions, keynotes and
poster sessions.
IJCLR 2020 invites paper submissions on all aspects of Learning and
Reasoning, on topics where machine learning is combined with machine
reasoning or knowledge representation.
There are two options for paper submissions, a Conference Track,
regarding submissions to one of the conferences/workshops participating
at IJCLR 2020, and a Journal Track, supported by the Machine Learning
Journal (MLJ). Papers accepted at the Journal Track will be published by
the MLJ and presented at IJCLR 2020.
*Paper submission dates:*
Journal Track 2nd cut-off date: April 20, 2020
Conference Track: May 29 2020
*Submission guidelines:*
http://lr2020.iit.demokritos.gr/papers/index.html
Topics of interest include, but are not limited to:
- Theory & foundations of logical & relational learning.
- Learning in various logical representations and formalisms, such as
logic programming &answer set programming, first-order & higher-order
logic, description logics & ontologies.
- Statistical Relational AI, including structure/parameter learning for
probabilistic logiclanguages, relational probabilistic graphical models,
kernel-based methods, neural-symbolic learning.
- Knowledge representation and reasoning in deep neural networks.
- Symbolic knowledge extraction from neural and statistical learning
models.- Explainable AI models, systems, and techniques that integrate
connectionist, statistical and symbolic paradigms.
- Neural-symbolic cognitive models.
- Inductive methods for program synthesis.
- Probabilistic programming.
- Combining logic and functional program induction.
- Meta-interpretative learning & predicate invention.
- Scaling-up logical & relational learning, parallel & distributed
learning, online learning and learning from data streams.
IJCLR 2020 Steering Committee:
Luc De Raedt, KU Leuven, Belgium
Stephen Muggleton, Imperial College London, UK
Artur d’Avila Garcez, City University of London, UK
Ute Schmid, University of Bamberg, Germany
Angelika Kimmig, Cardiff University, UK
Cèsar Ferri, Universitat Politènica de València, Spain
Jay Pujara, University of Southern California, USA
Sebastijan Dumančić, KU Leuven, Belgium
Nikos Katzouris, NCSR "Demokritos", Greece
Alexander Artikis, University of Pireaus & NCSR "Demokritos", Greece
_______________________________________________
uai mailing list
uai@ENGR.ORST.EDU
https://secure.engr.oregonstate.edu/mailman/listinfo/uai
