Probabilistic logic programming 2016

An ILP workshop

London, UK - 3 September 2016

NEW: Special issue

There will be a special issue on Probabilistic Logic Programming in the International Journal of Approximate Reasoning (IJAR). We welcome submissions of (improved/extended versions of) papers that were presented at the workshop in London, as well as new submissions on all topics of the workshop. For more information, please see the call for papers at the website of IJAR.

Deadline: March 1, 2017


9:30-10:30Invited talk: Deductive and Inductive Probabilistic Programming. Fabrizio Riguzzi
10:30-11:00Coffee break
11:00-11:30Fabio Cozman and Denis Mauá. The Structure and Complexity of Credal Semantics
11:30-12:00Marco Alberti, Elena Bellodi, Giuseppe Cota, Evelina Lamma, Fabrizio Riguzzi and Riccardo Zese. Probabilistic Constraint Logic Theories
12:00-12:30Arjen Hommersom and Marcos L.P. Bueno. Toward Computing Conflict-Based Diagnoses in Probabilistic Logic Programming
12:30-14:00Lunch break
14:00-15:00Invited talk: Probabilistic Inductive Logic Programming Based on Answer Set Programming. Matthias Nickles
15:00-15:30Christian Theil Have, Emil Vincent Appel, Ole Torp Lassen and Jette Bork-Jensen. Sampling Random Bioinformatics Puzzles Using Adaptive Probability Distributions
15:30-16:00Nicos Angelopoulos. Notes on the implementation of FAM


The proceedings can be found at CEUR.


Probabilistic logic programming (PLP) approaches have received much attention in this century. They address the need to reason about relational domains under uncertainty arising in a variety of application domains, such as bioinformatics, the semantic web, robotics, and many more. Developments in PLP include new languages that combine logic programming with probability theory as well as algorithms that operate over programs in these formalisms.

PLP is part of a wider current interest in probabilistic programming. By promoting probabilities as explicit programming constructs, inference, parameter estimation and learning algorithms can be ran over programs which represent highly structured probability spaces. Due to logic programming's strong theoretical underpinnings, PLP is one of the more disciplined areas of probabilistic programming. It builds upon and benefits from the large body of existing work in logic programming, both in semantics and implementation, but also presents new challenges to the field. PLP reasoning often requires the evaluation of large number of possible states before any answers can be produced thus breaking the sequential search model of traditional logic programs.

While PLP has already contributed a number of formalisms, systems and well understood and established results in: parameter estimation, tabling, marginal probabilities and Bayesian learning, many questions remain open in this exciting, expanding field in the intersection of AI, machine learning and statistics.

This workshop aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications. Interactions between theoretical and applied minded researchers are encouraged. The presence of this workshop at ILP is intended to encourage collaboration with researchers from the field of Inductive Logic Programming.


The workshop will take place at Room 060A of the Skempton Building of Imperial College, Prince Consort Rd, South Kensington, London.


The fee for participating in PLP'16 is GBP40, which includes coffee with pastry in the morning. To register for PLP'16, please send an email to with your name, affiliation, and address (which will appear on the receipt). To keep the cost of the workshop to a minimum, we request that you do pay the fee in cash during the workshop to one of the chairs.

Deadline for registration: 28 August 2016

Invited talks

Fabrizio Riguzzi: Deductive and Inductive Probabilistic Programming
Probabilistic programming (PP) is available in two different variants: imperative/functional and logic. These two variants have complementary strengths and mostly separate communities. In this talk I will discuss how most strengths of inference for imperative/functional PP can be included in PLP. Moreover, I will show that PLP is particularly suitable for inductive reasoning.
Matthias Nickles: Probabilistic Inductive Logic Programming Based on Answer Set Programming
Answer Set Programming (ASP) is a form of declarative programming based on the concept of so-called stable models of programs, with roots in logic programming and nonmonotonic reasoning. ASP has emerged as a fully declarative programming paradigm which provides significant advantages in areas such as search and optimization problem solving, common sense knowledge representation, and modeling of nondeterminism. In my talk, I will describe how ASP can be used as a basis for expressive probabilistic inductive logic programming, and the features (and challenges) of this direction. After introducing ASP and providing an overview of existing approaches to probabilistic declarative programming based on stable model semantics, I will present a recent framework for probabilistic inductive ASP which provides a high level of expressiveness (including the option to use first-order formulas with probabilities) in combination with a high degree of adaptability to a variety of tasks. I will discuss algorithms for inference and machine learning in this framework and their respective performance characteristics, and present possible applications of our framework. The last part of my talk will outline directions for future research in this area.


Papers due: Fri, 10 24 June 2016 (EXTENDED)
Notification to authors: Fri, 15 July 2016
Camera ready version due: Fri, 29 July 2016
Registration deadline: Sun, 28 August 2016
Workshop date: Sat, 3 September 2016

(the deadline for all dates is 23:59 BST)

Paper submissions

Full papers: 6-12 pages, short communications 2-5 pages.

Submissions site: easychair.
Call for papers: txt.

Programme committee


Programme committee

Samer Abdallah (University College London) [co-chair]
Arjen Hommersom (Open University of the Netherlands) [co-chair]

Elena Bellodi (University of Ferrara, Italy)
Hendrik Blockeel (KU Leuven, Belgium)
Yoshitaka Kameya (Meijo University, Japan)
Wannes Meert (KU Leuven, Belgium)
Alina Paes (Universidade Federal Fluminense, Brazil)
C. R. Ramakrishnan (University at Stony Brook, US)
Taisuke Sato (NII/SONAR, Japan)
Christian Theil Have (Copenhagen University, Denmark)
Herbert Wiklicky (Imperial College London, UK)
Nicola di Mauro (University of Bari, Italy)
Senior Committee
Nicos Angelopoulos (14M Genomics & Imperial College, UK)
Vitor Santos Costa (Universidade do Porto, Portugal)
James Cussens (University of York, UK)
Angelika Kimmig (KU Leuven, Belgium)
Evelina Lamma (University of Ferrara, Italy)
David Poole (University of British Columbia, Canada)
Luc De Raedt (KU Leuven, Belgium)
Fabrizio Riguzzi (University of Ferrara, Italy)
Alessandra Russo (Imperial College, UK)
Joost Vennekens (KU Leuven, Belgium)

Last modified: Wed 3 August 2016