Call for Papers: Learning and Reasoning 2022
Call for Papers
Machine Learning Journal, Special Issue on Learning and Reasoning
This special issue is motivated by the increased popularity of the hybrid approaches that combine learning and reasoning in the artificial intelligence and machine learning communities. Integrating learning and reasoning constitutes one of the key open questions in AI and 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. Integrating learning and reasoning calls for approaches that combine knowledge representation and machine reasoning techniques with learning algorithms from the fields of neural, statistical and relational learning.
Several subfields are actively pursuing research on Learning and Reasoning, and their integrations:
- Inductive Logic Programming (ILP), which studies machine learning within a logic programming context.
- Neuro-symbolic computation (NeSy), which is concerned with the integration of neural networks with logical reasoning abilities.
- Inductive Programming (IP), which studies the induction and synthesis of programs from examples of their input / output behaviour.
- Human-Like Computing (HLC), which aims to endow machines with human-like perceptual, reasoning and learning abilities which support collaboration and communication with human beings.
We solicit submissions on all aspects of Learning and Reasoning, on all topics where machine learning is combined with machine reasoning or knowledge representation. Topics 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 logic & ontologies.
- Statistical Relational AI, including structure/parameter learning for probabilistic logic languages, relational probabilistic graphical models, kernel-based methods, neural-symbolic learning.
- Systems and techniques that integrate neural, statistical & symbolic learning.
- Systems and techniques addressing aspects of integrating learning, reasoning & optimization.
- Knowledge representation and reasoning in deep neural networks.
- Symbolic knowledge extraction from neural and statistical learning models.
- Neural-symbolic cognitive models.
- Techniques that foster explainability & trustworthiness of AI models, including combinations of machine learning with constraints & satisfiability, explainable AI frameworks and reasoning about the behaviour of machine learning models.
- Inductive methods for program synthesis.
- Example-driven programming.
- Combining logic and functional program induction.
- Meta-interpretative learning & predicate invention.
- Scaling-up logical & relational learning: parallel & distributed learning techniques, online learning and learning structured representations from data streams.
- Human-Like Computing, including Cognitive and AI aspects of perception, action and learning
Authors are invited to submit novel, high-quality work that has neither appeared in, nor is under consideration for publication by other journals or conferences. Accepted papers will be part of the journal track of the 2nd International Joint Conference on Learning and Reasoning (https://ijclr22.doc.ic.ac.uk/), which will be held in Cumberland Lodge, Windsor Great Park, United Kingdom, 28-30 September 2022. Authors of accepted papers will be invited to present their work at the conference.
The editorial team will be aiming for a turn-around time of 10-12 weeks for most submissions. Articles should preferably be no longer than 20 pages. Submissions exceeding this length will not be given priority during reviews and will be under review for a longer period but will still be considered for the special track.
Papers must be prepared in accordance to the Journal guidelines:
http://www.springer.com/10994. A full range of general questions about submissions to Springer journals can be found here: https://www.springer.com/gp/authors-editors/journal-author
Manuscripts must be submitted to: http://MACH.edmgr.com An article is submitted to this special issue by choosing "S.I. LR 2022" as the article type.
Upcoming submission cut-off dates: 1st Feb 2022, 1st May 2022, 1st Aug 2022
Submission guidelines: https://ijclr22.doc.ic.ac.uk/call.htm
The Special Issue Guest Editors:
Alireza Tamaddoni-Nezhad, University of Surrey, UK (Lead Guest Editor)
Alan Bundy, University of Edinburgh, UK
Luc De Raedt, KU Leuven, Belgium
Artur d’Avila Garcez, City University of London, UK
Sebastijan Dumančić, Delft University of Technology, the Netherlads
Cèsar Ferri, Universitat Politènica de València, Spain
Pascal Hitzler, Kansas State University, USA
Nikos Katzouris, National Center for Scientific Research, Greece
Denis Mareschal, Birkbeck College, University of London, UK
Stephen Muggleton, Imperial College London, UK
Ute Schmid, University of Bamberg, Germany
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