Keynote Talk: Meta-Interpretive Learning: Achievements and Challenges

April 19, 2017 9:39 AM
Stephen Muggleton ( ) from Imperial College London is a professor of Machine Learning and Director of Syngenta University Innovation Centre on Systems Biology.

Meta-Interpretive Learning (MIL) is a recent Inductive Logic Programming technique aimed at supporting learning of recursive definitions.

A powerful and novel aspect of MIL is that when learning a predicate definition it automatically introduces sub-definitions, allowing decomposition into a hierarchy of reuseable parts. MIL is based on an adapted version of a Prolog meta-interpreter. Normally such a meta-interpreter derives a proof by repeatedly fetching first-order Prolog clauses whose heads unify with a given goal. By contrast, a meta-interpretive learner additionally fetches higher-order meta-rules whose heads unify with the goal, and saves the resulting meta-substitutions to form a program.

This talk will overview theoretical and implementational advances in this new area including the ability to learn Turing computabale functions within a constrained subset of logic programs, the use of probabilistic representations within Bayesian meta-interpretive and techniques for minimising the number of meta-rules employed.

The talk will also summarise applications of MIL including the learning of regular and context-free grammars, learning from visual representions with repeated patterns, learning string transformations for spreadsheet applications, learning and optimising recursive robot strategies and learning tactics for proving correctness of programs. The talk will conclude by pointing to the many challenges which remain to be addressed within this new area.

Keynote Talk: The Secret Life of Rules in Software Engineering

April 11, 2017 9:16 AM
Jordi Cabot (IN3-UOC, Barcelona, will give an interesting talk explaining how UML + OCL can largely be used for rule modelling in software engineering.

Explicit definition and management of rules is largely ignored in most software development projects. While the most “popular” software modeling language (UML) enjoys some measure of success in real-world software projects, its companion, the Object Constraint Language (the OMG standard to complement UML models with textual constraints and derivation rules) is largely ignored. As a result, rules live hidden in the code, implemented in an ad-hoc manner.
This somehow worked when data was mostly stored in relational databases and DBAs could at least enforce some checks on that data. But now, data lives in the open (e.g., data as a service, big data), accessible in a variety of formats (NoSQL, APIs, CSVs,…). This evolution facilitates the consumption and production of data but puts at risk any piece of software accessing it, at least in case no proper knowledge of the structure, quality and content of that data is available. And with the emergence of open data, it’s not only the software who accesses the data but people as well.
In the talk, he argues that rules must become first-class citizens in any software development project and describe our initiatives in discovering, representing and enforcing rules on (open and/or semi-structured) data.

Announcing RuleML+RR 2017 Tutorials

February 27, 2017 3:27 PM
  • Decision Modeling with DMN and OpenRules, by Jacob Feldman
  • How to do it with LPS (Logic-Based Production System), by Robert Kowalski, Fariba Sadri, Miguel Calejo
  • Semantic Event Reasoning and Rule-based Complex Event Processing, by Danh Le Phuoc, Adrian Paschke, Minh Dao-Tran, Marcin Wylot
  • Logic-based Rule Learning for the Web of Data, by Francesca A. Lisi
  • Rulelog: Highly Expressive Semantic Rules with Scalable Deep Reasoning, by Benjamin Grosof, Michael Kifer, Paul Fodor

New submission deadline of 2017: 6 March

February 27, 2017 3:22 PM

Due to popular demand, we have extended the submission deadline of RuleML+RR 2017 to 6 March. We encourage both long and short papers.

RuleML+RR 2017, held in London, 12-15 July, includes the following:

RuleML+RR 2017: Call for Tutorials

January 13, 2017 8:20 PM
Tutorials may introduce novices to major topics in the area, introduce experts to a special subarea, motivate and explain a topic of emerging importance, survey a mature area of research and/or practice, present a novel synthesis combining distinct lines of work, introduce the audience to an external topic that can relate to research in the area on a relevant topic.

Tutorial attendance is complimentary for all RuleML+RR 2017 conference registrants.


Tutorial proposals should be submitted via Easychair:

Each submission (up to two pages) should include the following information:

  • A title.
  • An abstract.
  • The preferred duration (up to half-day).
  • A description that outlines which topics would be covered, and the depth to which they would be covered. If different length options are possible, the proposal should identify which parts would be included for each length.
  • A short description of the intended audience and any prerequisite knowledge for attendees.
  • A brief biography of the proposed presenter(s), along with contact information.
  • If (part of) the tutorial material or an earlier version of it has been presented elsewhere, the proposal should indicate those respective events (and dates), and describe how the current proposal differs from the previous ones.

A two-page extended abstract of the tutorial will be included in the conference proceedings. Tutorial slides are expected to be made available online to conference participants.


Proposal submission: 20 January 2017

Notification: 6 February 2017

Camera-ready due: 24 April 2017

Possible tutorial dates: 12, 13, 14, 15 July 2017


The RuleML+RR 2017 program chairs: Stefania Costantini (University of L’Aquila, Italy), Enrico Franconi (Free University of Bozen-Bolzano, Italy), William Van Woensel (Dalhousie University, Canada);

The RuleML+RR 2017 General Chairs: Roman Kontchakov (Birkbeck, University of London, UK), Fariba Sadri (Imperial College London, UK);

Publicity Chair: Giovanni De Gasperis (University of L'Aquila, Italy).