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CALL FOR PAPER
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2nd International Workshop on Learning and NonMonotonic Reasoning (LNMR 2015)
http://lnmr2015.insight-centre.org/

27-30 September 2015, Lexington, KY, USA

co-located with the
13th International Conference on Logic Programming and
Nonmonotonic Reasoning (LPNMR 2015)
http://lpnmr2015.mat.unical.it/
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*Aims and scope

Knowledge representation and reasoning (KR&R) and machine learning are two important fields in artificial intelligence (AI). (Nonmonotonic) logic programming (NMLP) and answer set programming (ASP) provide formal languages for representing and reasoning with commonsense knowledge and realize declarative problem solving in AI. On the other side, inductive logic programming (ILP) realizes inductive machine learning in logic programming, which provides a formal background to inductive learning and the techniques have been applied to the fields of relational learning and data mining. Generally speaking, NMLP and ASP realize nonmonotonic reasoning while lack the ability of (inductive) learning. By contrast, ILP realizes inductive machine learning while most techniques have been developed under the classical monotonic logic. With this background, some researchers attempt to combine techniques in the context of nonmonotonic inductive logic programming (NMILP). Such combination will introduce a learning mechanism to programs and would exploit new applications on the NMLP side, while on the ILP side it will extend the representation language and enable to use existing solvers. Cross-fertilization between learning and nonmonotonic reasoning can also occur in areas including but not limited to:

- the use of answer set solvers for Inductive Logic Programming
- speed-up learning while running answer set solvers
- learning action theories
- learning transition rules in dynamical systems
- learning normal, extended and disjunctive programs
- formal relationships between learning and nonmonotonic reasoning
- abductive learning
- updating theories with induction
- learning biological networks with inhibition
- applications involving default and negation

This workshop follows from its first edition in 2013 in an attempt to provide an open forum for the identification of problems and discussion of possible collaborations among researchers with complementary expertise. To facilitate interactions between researchers in the areas of (machine) learning and nonmonotonic reasoning, we welcome contributions focusing on problems and perspectives concerning both learning and nonmonotonic reasoning.

*Submissions

We solicit original papers which are not published elsewhere. Papers should be written in English and be formatted according to the Springer Verlag LNCS style, which can be obtained from http://www.springeronline.com. Every paper should not exceed 12 pages including the title page, references and figures. All submissions will be peer-reviewed and all accepted papers must be presented at the workshop. Paper submission will be electronic through the LNMR-15 Easychair site: https://easychair.org/conferences/?conf=lnmr2015.

*Proceedings

Workshop organizers are considering to publish an on-line proceedings in a formal way. The details will be announced later. Based on the quality of submissions, a special journal issue will also be considered.

*Important Dates
Paper registration: June 22
Submission deadline: June 29
Notification: August 17
Final version due: September 1
Workshop: 1 or 2 days in September 27-30

*Workshop co-Chairs

Alessandra Mileo, INSIGHT Centre for Data Analytics, NUI Galway, Ireland
Alessandra Russo, Dept. of Computing, Imperial College London, UK

*Program Committee

- Mario Alviano University of Calabria, Italy
- Katsumi Inoue (National Institute of Informatics, Japan)
- Francesca A. Lisi (Università degli Studi di Bari "Aldo Moro", Italy)
- Chiaki Sakama (Wakayama University, Japan)
- Dalal Alrajeh (Imperial College London, UK)
- Marcello Balduccini (Kodak Research Laboratories, USA)
- Matthias Nickles NUI Galway, Ireland
- Gauvain Bourgne (Université Pierre et Marie Curie, France)
- Adrian Pearce (University of Melbourne, Australia)
- Taisuke Sato (Tokyo Institute of Technology, Japan)