| Subject: | [WI] KR2020 & ML - CFP |
|---|---|
| Date: | Thu, 09 Jan 2020 19:30:32 +0200 |
| From: | Theofanis I. Aravanis <taravanis@upatras.gr> |
| Reply-To: | Theofanis I. Aravanis <taravanis@upatras.gr> |
| Organization: | University of Patras |
| To: | taravanis@upatras.gr |
Call for Papers
**Special Session on Knowledge Representation and Machine
Learning**
at the 17th International Conference on Principles of Knowledge
Representation and Reasoning (KR2020)
September 12-18th, 2020
Rhodes, Greece
https://kr2020.inf.unibz.it/
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Important Dates
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Submission of title and abstract: 4 March 2020
Paper submission deadline: 11 March 2020
Author response period: 4--6 May 2020
Notification: 27 May 2020
Camera-ready papers: 24 June 2020
Conference dates: 12--18 September 2020
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Description
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Over the last two decades Machine Learning (ML) has made
incredible advancements showing to be very effective in solving
specific tasks and robust in many experimental learning
applications. Deep learning, statistical (relational) learning,
reinforcement learning and (logic-based and/or probabilistic)
learning are among the many ML approaches that are witnessing
such advancements. On the other hand, Knowledge Representation
and Reasoning (KR) has continued to be at the core of Artificial
Intelligence (AI) research providing solutions for explicit
declarative representation of knowledge and knowledge-based
inference, which have theoretical and practical relevance in
many aspects of AI as well as in new emerging fields outside AI.
The synergy between these two areas of AI has the potential to
unlock new advancements on foundations of AI that offer new
insights into open fundamental challenges included, but not
limited to, learning symbolic generalisations from raw
(multi-modal) data, using knowledge to facilitate data-efficient
learning, supporting interpretability of learned outcomes,
federated multi-agent learning and decision making.
This year, for the first time, KR2020 will host a special
session on "Knowledge Representation and Machine Learning". This
special session aims at providing researchers and industrial
practitioners with a dedicated forum for presentation and
discussion of new ideas, research experience and emerging
results on topics related to computational learning and symbolic
knowledge representation and reasoning. This special session
provides the opportunity for fostering meaningful connections
between researchers from these two main areas of AI and, at the
same time, offering the possibility to learn about progress made
on these topics, share their own views and learn about
approaches that could lead to effective cross-fertilisation
among research in ML and KR and new innovative solutions to key
AI research challenges.
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Expected contributions
----------------------
The Special Session on KR and ML at KR2020 invites submissions
of papers across KR and ML on advancements in one of these areas
for the purpose of addressing open research challenges in the
other, integration of computational learning and knowledge
representation and reasoning, and the application of combined KR
and ML approaches to solve real-world problems, including case
studies and benchmarks.
We welcome papers on a wide range of topics, including but not
limited to:
-- Learning ontologies and knowledge graphs
-- Learning action theories
-- Learning common-sense knowledge
-- Learning spatial and temporal theories
-- Learning preference models
-- Learning causal models
-- Learning tractable probabilistic models
-- Probabilistic reasoning and learning
-- Graphical models for knowledge representation and reasoning
-- Reasoning and learning over knowledge graphs
-- Logic-based learning algorithms
-- Neural-symbolic learning
-- Statistical relational learning
-- Multi-agent learning
-- Machine learning for efficient knowledge inference
-- Symbolic reinforcement learning
-- Learning symbolic abstractions from unstructured data
-- Machine-learning-driven reasoning algorithms
-- Explainable AI
-- Transfer learning
-- Multi-agent learning
-- Expressive power of learning representations
-- Knowledge-driven natural language understanding and dialogue
-- Knowledge-driven decision making
-- Knowledge-driven intelligent systems for internet of things
and cybersecurity
-- Application of knowledge-driven ML to question answering and
story understanding
-- Application of knowledge-driven ML to Robotics
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Submission Guidelines and Evaluation Criteria
---------------------------------------------
The special session emphasizes KR and ML, and welcomes
contributions that extend the state of the art at the
intersection of KR and ML. Therefore, KR-only or ML-only
submissions will not be accepted for evaluation in this special
session.
Submissions will be rigorously peer reviewed by PC members, who
are active in KR and ML. Submissions will be evaluated on the
basis of the overall quality of their technical contribution,
including criteria such as originality, soundness, relevance,
significance, quality of presentation, and understanding of the
state of the art.
In this special session, the selection process of the highest
quality papers will apply the following criteria:
* Importance and novelty of using knowledge representation and
reasoning to advance machine learning, or novelty of using
machine learning solutions to advance knowledge representation
and reasoning.
* Applicability of the proposed solutions in real-world.
* Reusability of datasets, case studies and benchmarks for
systems and/or application papers.
* Proved theoretical or empirically demonstrated practical
advancement of the proposed solution with respect to baseline
pure KR or ML approaches.
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Chairs
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Alessandra Russo (Imperial College London, UK)
Guy Van den Broeck (UCLA, USA)