CALL FOR PAPERS

PLP 2023: The Tenth Workshop on Probabilistic Logic Programming

                    A Workshop of 39th International Conference on Logic Programming                      

July 09-15, 2023

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.

The workshop encompasses all aspects of combining logic, algorithms, programming and probability.

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 run 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. As is traditional in this series, the workshop would be designed to foster exchange between the various communities relevant to probabilistic logic programming, including probabilistic programming and statistical relational artificial intelligence.

Submission Guidelines

Contributions should be prepared in the LNCS style (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines). A mixture of papers are sought including: new results; work in progress; and technical summaries of recent substantial contributions.  Papers presenting new results should be 6-15 pages in length. Work inprogress and technical summaries can be shorter (2-5 pages).

At least one author of each accepted paper will be required to attend the workshop to present the contribution.

List of Topics

• probabilistic (logic) programming formalisms

• probabilistic (logic) programming languages

• parameter estimation

• statistical inference

• implementations

• structure learning

• reasoning with uncertainty

• constraint store approaches

• stochastic and randomised algorithms

• probabilistic knowledge representation and reasoning

• neuro-symbolic representation and reasoning

• constraints in statistical inference

• PLP applications, such as bioinformatics, semantic web, robotics,...

• lifted probabilistic graphical models

• (lifted) Bayesian learning

• tabling for learning and stochastic inference

• sampling methods

• stochastic search

• labelled logic programs

• weighted model counting

• knowledge compilation

• integration of statistical software

  This list is by no means exhaustive.

Committees

Programme Committee Chairs

• Kilian Rückschloß
• Felix Weitkämper, DPhil (Oxon)

Programme Committee

• Rafael Kiesel, TU Wien
• Sagar Malhotra, Fondazione Bruno Kessler
• Dr. Nico Potyka, Imperial College London
• Dr. Vaishak Belle, University of Edinburgh
• Prof. Elena Bellodi, Associate Professor, University of Ferrara
• Prof. Fabio Cozman, Full Professor, Universidade de São Paulo
• Dr. Matthias Nickles, Lecturer Above the Bar, NUI Galway
• Dr. Roberta Calligari, Postdoc, Università di Bologna
• Prof. Fabrizio Riguzzi, University of Ferrara
• Dr. Damiano Azzolini, University of Ferrara
• Dr. Peter Baumgartner, Data61/ANU canberra
• Theresa Swift PhD, Universidad Nova de Lisboa
• Prof. Alexander Artikis, University of Piraeus

Invited Speakers

• Dr. Devendra Singh Dhami, Independent Research Group Leader and Post Doctoral Researcher, hessian.AI and AIML Lab, TU Darmstadt
• Prof. Rafael Peñaloza, Associate Professor, University of Milano-Bicocca
• Prof. Joost Vennekens, Associate Professor, KU Leuven

Publication

Informal proceedings will be made available electronically to attendees and submitted to the CEUR Workshop Proceedings repository (http://ceur-ws.org/).

Venue

The workshop will be held at the Imperial College London.

Contact

All questions about submissions should be emailed to kilian.rueckschloss@lmu.de or to felix.weitkaemper@lmu.de.