1st TAILOR Workshop at ECAI 2020, Aug 29-30, Santiago de Compostela
https://liu.se/en/research/tailor
Submission deadline: June 4, 2020 (AOE)
Notification of acceptance: June 23, 2020
Camera ready paper: July 23, 2020 (AOE)
Submission link: https://easychair.org/conferences/?conf=tailor2020
In the case that ECAI turns into an online event, we are making plans
for taking advantage of the different format. The intention is to do the
best of the situation, no matter if it is a physical or an online event.
The current scientific landscape is fragmented with many research groups
working individually or in smaller constellations in often relatively
isolated scientific communities: machine reasoning, machine learning,
and optimization are examples of such mostly-disjoint communities.
The TAILOR workshop will bring these groups and researchers together in
a unique atmosphere to discuss the state of the art and the latest
advances in the integration of learning, optimisation and reasoning to
provide the scientific foundations for Trustworthy AI.
The TAILOR community builds upon a large H2020 proposal on building a
network of centers of excellence that includes over 100 labs in Europe.
The TAILOR network of research excellence centers focus on the
scientific foundations of Trustworthy AI integrating learning,
optimisation and reasoning.
The main scientific topics are:
* Trustworthiness: How to learn fair AI models, even in spite of biased
data? How to develop explainable and interpretable AI decision
processes? How to develop transparent AI systems and integrate them into
the decision process for increasing user trust?
* Learning, reasoning and optimisation: How to integrate AI paradigms
and representations for reasoning, learning and optimisation in order to
support trustworthy AI? Integrated approaches to learning, reasoning and
optimisation should allow AI systems to bridge the gap between low-level
perception and high-level reasoning, to combine knowledge-based and
data-driven methods, to explain their behaviour and allow for
introspection of the resulting models.
* Deciding and Learning How to Act. How to empower an AI system with the
ability of deliberating how to act in the world, reasoning on the
effects of its actions, learning from past experiences, as well as
monitoring the actual or simulated outcome of its actions, learning from
possibly unexpected outcomes, and again reasoning and learning how to
deal with such new outcome?
* Reasoning and Learning in Social Contexts. Agents should not reason,
learn and act in isolation. They will need to do it with others and
among others. So, this topic is concerned with how AI systems should
communicate, collaborate, negotiate and reach agreements with other AI
and (eventually) human agents within a multi-agent system (MAS).
* AutoAI: How to build AI tools, systems, and infrastructure that are
performant, robust and trustworthy including having the ability to
configure and tune itself for optimal performance? How can we support
(1) people with limited AI expertise and (2) highly-skilled experts in
building such AI systems?
We welcome submissions to the workshop of the following types:
1. Presentations of relevant work that has recently been published or
has already been accepted for publication in journals such as AIJ, JAIR,
JMLR, MLJ, and major conferences such as AAAI, ICML, IJCAI, NeurIPS,
SIGKDD, etc. The submission should in this case only consist of a copy
of the accepted paper.
2. Long papers reporting on new material. Papers can be at most 16 pages
in the Springer LNCS format. Please note that also shorter papers are
welcome.
3. Extended abstracts that report on novel and preliminary ideas.
Extended abstracts can be at most 6 pages in LNCS format.
4. Short position statements on the topic of the workshop, at most 6
pages in LNCS format.
The workshop is interested in foundational as well as more applied
contributions. What matters is that they address the topics of the
workshop - the integration of learning, optimisation and reasoning to
provide the scientific foundations for Trustworthy AI.
Both long and short papers must be formatted according to LNCS
guidelines
(https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines)
and submitted electronically through EasyChair:
https://easychair.org/conferences/?conf=tailor2020
Papers accepted for TAILOR 2020 will be published in a Springer LNCS
post proceedings.
Organisers
Workshop Chair Fredrik Heintz, fredrik.heintz@liu.se, Linköping
University, Sweden
Luc De Raedt, KU Leuven, Belgium
Peter Flach, University of Bristol, UK
Hector Geffner, ICREA and Universitat Pompeu Fabra, Spain
Fosca Gianotti, National Research Council, Pisa, Italy
Holger Hoos, Leiden University, The Netherlands
Michela Milano, University of Bologna, Italy
Barry O'Sullivan, University College Cork, Ireland
Ana Paiva, University of Lisbon, Portugal
Marc Schoenauer, INRIA, France
Philipp Slusallek, DFKI, Germany
Joaquin Vanschoren, Eindhoven University of Technology, The Netherlands
Program Committee
Maria Garcia De La Banda, Monash University, Australia
Randy Goebel, U Alberta, Canada
Lars Kotthoff, University of Wyoming, USA
Andrea Lodi, École Polytechnique de Montréal, Canada
Francesca Rossi, IBM, USA
Sylvie Thiebaux, ANU, Australia
Pascal Van Hentenryck, Georgia Institute of Technology, USA
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