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CI 2019 : Workshop on Computational Intelligence
CI 2019 : Workshop on Computational Intelligence

CI 2019 : Workshop on Computational Intelligence

Kassel
Event Date: September 24, 2019 - September 24, 2019
Abstract Submission Deadline: July 14, 2019
Submission Deadline: July 21, 2019
Notification of Acceptance: August 15, 2019
Camera Ready Version Due: August 21, 2019




Call for Papers

CFP: Workshop on Computational Intelligence

Aims and Scope
We apply Artificial Intelligence in ever more application domains but AI still lacks the adaptability and resilience of most biological systems. One of those gaps is probabilistic reasoning and decision making. Nature as a paragon brings fuzzy reasoning, neuronal networks, and learning together, e.g., to decide on a fight-or-flight response. The inspiration of Computational Intelligence originating from natural systems, therefore, aims at closing this gap with theoretical results as well as applying them in real-world applications.

Call for Papers
Like the IEEE Computational Intelligence Society which describes its focus as "the theory, design, application, and development of biologically and linguistically motivated computational paradigms emphasizing neural networks, connectionist systems, genetic algorithms, evolutionary programming, fuzzy systems, and hybrid intelligent systems in which these paradigms are contained" the Workshop on Computational Intelligence aims to bring together scientists and specialist form industry to tackle some of the challenges of AI and their application. Thus, we invite you to submit original research and application papers including but not limited to the following topics:

Fuzzy logic:
Probabilistic models of meaning Probabilistic reasoning Fuzzy inference Decision making in uncertainty Evaluation of Probabilistic Models

Neuronal Networks:
Generalizations of neuronal networks Explainable ANN Spreading Activation Neuroevolution

Evolutionary computations:
Online Genetic Algorithms ANN and generational learning Biased Genetic Algorithms Transfer learning with GA

Learning theory:
Adversarial Learning Reinforcement Learning Abductive Deductive Reasoning

PC:

Prof. Dr. Johannes Fähndrich (Hochschule für Polizei BW)
Dr. Sebastian Ahrndt (Curamatik UG)
Prof. Dr. Engelbrecht (Stellenbosch University)
Prof. Dr. rer. nat. Frank Hoffmann (TU Dortmund)
Prof. Dr. Frank Klawonn (Ostfalia Hochschule für angewandte Wissenschaften)
Prof. Dr. rer. nat. habil. Rudolf Kruse (Universität Magdeburg)

Workshop website: www.ci2019.fähndrich.de
The workshop is part of the KI 2019 conference. The KI 2019 conference takes place in Kassel, Germany, September 23th-26th 2018, and will be held in conjunction with the 49th Annual Conference of the German Computer Science Association: INFORMATIK 2019 (http://informatik2019.de).

Submission Guidelines
We invite papers, which have to be in English and formatted according to the Springer LNCS style, in the following category:
Full technical papers (12 pages max., excluding references) are expected to report on new research that makes a substantial technical contribution to the field. Additional details may be included in an appendix, which, however, will be read at the discretion of the PC.

Important Dates
July 14: Abstract submission
July 21: Paper submission
August 15: Notifications
August 21: Final versions

Submission will be through the EasyChair conference management system. The submission link is: https://easychair.org/conferences/?conf=ci20190.
Full papers and technical communications will be subject to blind peer review based on the standard criteria of relevance, the significance of results, originality of ideas, soundness, and quality of the presentation. Papers accepted in this process will be published in the main conference proceedings, published by Springer in the LNAI Lecture Notes of Artificial Intelligence series will be presented at the conference. At least one author of each accepted paper must register for the conference and present the contribution.



Credits and Sources

[1] CI 2019 : Workshop on Computational Intelligence


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