[PlanetKR] IJCAI 2017 Workshop on Logical Foundations for Uncertainty and Learning

Vaishak Belle vaishak at cs.toronto.edu
Fri Mar 24 17:39:49 EST 2017

Preliminary Call for Papers

IJCAI 2017 Workshop on Logical Foundations for Uncertainty and Learning



The purpose of this workshop is to promote logical foundations for
reasoning and learning under uncertainty. Uncertainty is inherent in many
AI applications, and coping with this uncertainty, in terms of preferences,
probabilities and weights, is essential for the system to operate
purposefully. In the same vein, expecting a domain modeler to completely
characterize a system is often unrealistic, and so enabling mechanisms by
means of which the system can infer and learn about the environment is
needed. While probabilistic reasoning and Bayesian learning has enjoyed
many successes and is central to our current understanding of the data
revolution, a deeper investigation on the underlying semantical issues as
well as principled ways of extending the frameworks to richer settings is
what this workshop strives for. Broadly speaking, we aim to bring together
the many communities focused on uncertainty reasoning and learning --
including knowledge representation, machine learning, logic programming and
databases -- by focusing on the logical underpinnings of the approaches and

Given the intent of the workshop, we encourage two categories of


   On the practical side, we solicit papers that propose ways to bridge
   conventional learning and inference techniques with deductive and inductive
   reasoning. Driven by the successes of relational graphical models and
   statistical relational learning, we especially encourage papers that
   emphasize or demonstrate non-standard logical features in systems, e.g. the
   ability to handle infinite domains, existential uncertainty and/or function

   On the foundations side, we solicit papers that explicate the use of
   weights in reasoning and learning, e.g. the use of weight functions such as
   degrees of belief, preferences, and truth degrees. We especially encourage
   papers that demonstrate how non-standard weight functions for reasoning and
   learning can be better integrated with existing probabilistic methods. The
   idea, then, is to foster collaboration between machine learning
   practitioners and the weighted logic community. For example, we encourage
   papers that revisit the learning objectives and inference methodologies of
   existing systems, and propose novel semantical frameworks to understand

In essence, this workshop builds on and extends the scope of the successful
series WL4AI (Weighted Logics for Artificial Intelligence: ECAI-2012,
IJCAI-2013, IJCAI-2015) in additionally looking at the semantical
 foundations of machine learning and exploring practical issues.

Topics include (but are not limited to):


   Probabilistic and weighted databases and knowledge bases

   Integration of deductive and inductive reasoning with Bayesian inference
   and learning

   Semantical foundations for machine learning

   Logics for data-intensive information processing, such as data fusion

   Extension of statistical relational learning with generic weight

   Declarative methods for inference and learning

Paper Format and Submission

We invite technical papers (up to 6 pages), position papers (up to 2

We invite submissions describing either work in progress or mature work
that has already been published at other research venues and would be of
interest to researchers working on the themes above. Submission of
previously published work in whole or in part may be in the form of a
resubmission of a previous paper, or in the form of a position paper that
overviews and cites a body of work.

All papers should be typeset in the IJCAI style, described at


Detailed instructions for submission will be available soon. Please see the
website for up to date information (including submission procedure):


Important Dates


   Paper Submission: May 8

   Author Notification: June 8

   Camera ready: July 15

   Workshop Date: August 19

Organizing Committee

Vaishak Belle, University of Edinburgh, vaishak(at)ed.ac.uk

[Contact Person]

Marcelo Finger, University of Sao Paulo, mfinger(at)ime.usp.br

James Cussens, University of York, james.cussens(at)york.ac.uk

Guilin Qi, Southeast University, China, gqi(at)seu.edu.cn

Henri Prade, Universite Paul Sabatier, France, prade(at)irit.fr

Lluis Godo, IIIA CSIC, Spain, godo(at)iiia.csic.es
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