PLP 2015
Probabilistic Logic Programming

Table of Contents

• Preface 1-6
  Fabrizio Riguzzi, Joost Vennekens

Invited Talks

• BIMS: for Bayesian Inference of Model Structure 7
  Nicos Angelopoulos
• Probabilistic (Logic) Programming: Opportunities and Challenges 8
  Angelika Kimmig

Presentations

• Advances in Integrating Statistical Inference 9 - 18
  Nicos Angelopoulos , Samer Abdallah , Georgios Giamas
  
• Towards a General Framework for Actual Causation Using CP-logic 19 - 38
  Sander Beckers , Joost Vennekens
  
• Most Probable Explanation for MetaProbLog and Its Application in Heart Sound Segmentation 39 - 45
  Theofrastos Mantadelis , Jorge Oliveira , Miguel Coimbra
  
• Constraint-Based Inference in Probabilistic Logic Programs 46 - 56
  Arun Nampally , Cartic R. Ramakrishnan
  
• A Hybrid Approach to Inference in Probabilistic Non-Monotonic Logic Programming 57 - 68
  Matthias Nickles , Alessandra Mileo
  
• The Distribution Semantics is Well-Defined for All Normal Programs 69 - 84
  Fabrizio Riguzzi
  
• Probabilistic Abductive Logic Programming using Dirichlet Priors 85 - 98
  Calin-Rares Turliuc , Luke Dickens , Alessandra Russo , Krysia Broda
  

Presented Papers which Appear Elsewhere

• Anytime Inference in Probabilistic Logic Programs with Tp-Compilation
  Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt
  International Joint Conference on Artificial Intelligence, 2015, AAAI Press / International Joint Conferences on Artificial Intelligence