PLP: Probabilistic Logic Programming
                    ------------------------------------

     A workshop of the 2014 International Conference on Logic Programming
                               17 July 2014
                              Vienna, Austria
                          http://stoics.org.uk/plp
           


Invited speaker:                James Cussens, University of York, UK
Deadline for submissions:       10th of May
Special issue:                  International Journal of Approximate Reasoning


Overview
-----
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 braking 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  provides a  forum for  the  exchange of ideas,  presentation of 
results and preliminary work, in the following areas 

   * probabilistic logic programming formalisms

   * parameter estimation

   * statistical inference

   * implementations

   * structure learning

   * reasoning with uncertainty

   * constraint store approaches

   * stochastic and randomised algorithms

   * probabilistic knowledge representation and reasoning

   * constraints in statistical inference

   * applications, such as

   * * bioinformatics

   * * semantic web

   * * robotics

   * probabilistic graphical models

   * Bayesian learning

   * tabling for learning and stochastic inference

   * MCMC

   * stochastic search

   * labelled logic programs

   * integration of statistical software

The above list should be interpreted broadly and is by no means exhaustive.

Purpose
-----
The main aim of the workshop is to provide a  platform for publishing results in
this area with emphasis on the LP aspects of PLP.The collocation  with ICLP will
benefit both the main conference and the workshop. We hope that both (a) more LP
researchers will become interested in inference and learning with PLP and 
(b)PLP 
researchers will get important feedback on their work from logic programmers.

Submissions
-----
Submissions will be  managed via EasyChair. Contributions should be  prepared in
the LLNCS style. A mixture  of papers are sought including: new results, work in
progress  as  well as technical  summaries of recent  substantial contributions.
Papers presenting  new results should  be 6-12 pages in length. Work in progress
and technical summaries  can be shorter. The workshop  proceedings will  clearly
indicate the type of each paper.

Deadlines
-----
Submission:           May 10
Notification:         May 31
Camera ready:        June 16
Workshop:            July 17
Journal subm.:       Oct.  6

Publication
-----
Proceedings will  be made available electronically to attendees.  They will also
be for stored  permanently in the form  of a booklet  on the  Computing Research
Repository (http://arxiv.org/corr/home/).  The  proceedings  will  constitute of
clearly  marked sections  corresponding to  the different  types of  submissions
accepted.A special issue including extended versions of selected workshop papers
will be published in the International Journal of Approximate Reasoning.

Legacy
-----
We hope that PLP will become an  annual event  and that  in the future  PLP will
alternate its collocation between ICLP and ILP.

Invited Speaker 
-----
James Cussens       (University of York, UK)

Programme committee
-----
Nicos Angelopoulos  (Imperial College, UK) [co-chair]
Elena Bellodi       (Universita di Ferrara, Italy)
Hendrik Blockeel    (Leiden University, The Netherlands)
Yoshitaka Kameya    (Meijo University, Japan) 
Angelika Kimmig     (KU Leuven, Belgium)   [co-chair]
Aline Paes          (Rio de Janeiro, Brazil)
Luc De Raedt        (KU Leuven, Belgium)
C. R. Ramakrishnan  (Stony Brook University, USA)
Fabrizio Riguzzi    (Universita di Ferrara, Italy)
Vitor Santos Costa  (Universidade do Porto, Portugal)
Taisuke Sato        (Tokyo Institute of Technology, Japan)
V. S. Subrahmanian  (University of Maryland, USA)
Terrance Swift      (New University of Lisboa, Portugal)
Herbert Wiklicky    (Imperial College, UK)
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