Download Special session Automation 2017

Machine Intelligence
A special session during the 21st AUTOMATION conference
15-17 March 2017, Warsaw, Poland
http://www.piap.pl/automation
Theme:
Artificial Intelligence (AI) enabled computers to perform some complex tasks that would normally require humanlevel intelligence. Three types of AI systems can be distinguished: Expert Systems (ES), Machine Learning (ML)
and Machine Intelligence (MI). Expert systems are traditional software systems, typically tailored for a given
domain and built on the knowledge of human experts. Machine Learning enabled the systems to learn from, and
continuously adapt to, data without being explicitly programmed for that kind of data and to move from one problem
domain to another with very few changes to their algorithmic core. Finally, Machine Intelligence systems gather
from machine learning, but additionally posses the ability to perceive and influence their environment, constantly
learning from the interactions with that environment about the consequences of their actions.
Recent progress in the field of MI enabled several spectacular successes. In particular, combinations of diverse
techniques enabled to reach super-human level of performance, e.g. IBM’s Watson crushing the world’s best players
in an American question-and-answer TV Jeopardy! in 2011, University of Alberta's Cepheus winning in heads-up
limit hold'em poker in 2015 or Google DeepMind's AlphaGo beating South Korean professional Go champion in
2016. But aside of those medial ones, AI technologies cut across a vast array of problems, such as computer vision,
natural language processing, language translation, or email security, and as a result are reshaping diverse areas of
business world, starting from health care (automated diagnostics, early disease detection based on genomics,
algorithmic drug discovery); agriculture (sensor- and vision-based intelligent systems, autonomous farming
vehicles); transportation and logistics (self-driving cars, drones, fleet management); robotics (robots learning
sophisticated manipulations skills); and financial services (advanced credit decisioning). The main goal of this
session is to bring together the Machine Intelligence theorists and practitioners to present and discuss the recent
advances in this field.
Scope:
The covered topics include, but are not limited to:
 application of various combinations of AI techniques in robotics, automation and measurement techniques,
including deep reinforcement learning, neural-based predictive control etc.
 new techniques and approaches to learning, such as end-to-end training, bootstrapping etc.
 novel biologically-inspired architectures and types of neural networks, e.g. neural networks with external
interfaces/memory, wide and deep neural nets etc.
We invite presentations of the work of both theoretical and experimental nature.
Paper submission:
The papers accepted for session will be published along with the rest of conference papers in the Springer's
Advances in Intelligent Systems and Computing (AISC) series (http://www.springer.com/series/11156), indexed in
Web of Science. Papers should be submitted via EasyChair system. Please follow the instructions on website:
http://www.piap.pl/automation/english/registration_of_interest.php.
Important dates:
October 10th, 2016 – Submission of papers
December 8th, 2016 – Notification of acceptance
Organizers:
Tomasz Kornuta, Ph.D.
IBM Research, Almaden
Prof. Cezary Zieliński, Ph.D., D.Sc.
Warsaw University of Technology, Institute of Control and Computation Engineering
Paweł Wawrzyński, Ph.D.
Warsaw University of Technology, Institute of Control and Computation Engineering