IEEE Symposium on

Evolving and Autonomous Learning Systems

The EALS 2018 Symposium will be a focal point for presentation of the recent advanced research results and industrial applications in the area of evolving and autonomously learning systems. The role of autonomous learning from (big) data (streams) is growing with the exponential explosion of amounts, complexity and hetero-genuous nature of the data we are living through. The traditional methods of machine learning, probabilistic and even computational intelligence techniques such as neural networks and fuzzy sets and systems require in practice a lot of handcrafting, make restrictive assumptions and are often not directly applicable to dynamically changing, evolving data with non-stationary properties, of hetero-genuous nature (mixing signals, image/video, text), categorical variables, etc. Extracting autonomously interpretable models which are not fixed, but dynamically evolving is a key challenges to be addressed. The Symposium has established track record and aims to keep and build upon this with the current event, EALS 2018.

The manuscripts should be submitted in PDF format. Click Here to know further guidelines for submission.


New Adaptive and Evolving Learning Methods:

  •    Evolving in Dynamic Environments
  •    Drift and Shift in Data Streams
  •    Self-monitoring Evolving Systems
  •    Evolving Decision Systems / Evolving Perceptions
  •    Self-organising Systems/ Evolving Neuro-fuzzy Systems
  •    Neural Networks with Evolving Structure
  •    Non-stationary Time Series Prediction with ES
  •    Automatic Novelty Detection in Evolving Systems
  •    Stability, Robustness, Unlearning Effects
  •    Structure Flexibility and Robustness in Evolving Systems
  •    Evolving Fuzzy Clustering Methods
  •    Evolving Fuzzy Rule-based Classifiers
  •    Evolving Intelligent Systems for Time Series Prediction
  •    Evolving Intelligent System State Monitoring and Prognostics
  •    Evolving Intelligent Controllers
  •    Evolving Fuzzy Decision Support Systems
  •    Evolving Consumer Behaviour Models

Real-world application:

  •    Robotics and Control Systems
  •    Industrial Applications
  •    Data Mining and Knowledge Discovery
  •    Intelligent Transport
  •    Bio-Informatics
  •    Defence

Symposium co-Chairs

Plamen Angelov

Lancaster University, UK

Dimitar Filev
Ford Motor Company, USA

Nikola Kasabov
Auckland University of Technology, New Zealand

Program Committee

Rashmi Dutta BaruahIIT, India
Abdelhamid BouchachiaUniversity of Bournemouth, UK
Bruno Sielly Jales CostaIFRN, Brazil
Richard Duroniversity of La Coruna, Spain
Fernando GomideUniversity of Campinas, Brazil
Xiaowei GuLancaster University, UK
Lazaros IliadisAristotle University of Thessaloniki, Greece
Jose Antonio IglesiasUniversity Carlos III, Spain
Janusz KacprzykPolish Academy of Sciences, Poland
Dmitry KanginUniversity of Exeter, UK
Edwin LughoferUniversity of Linz, Austria
Moamar Sayed MouchawehUniversity of Reims, France
Radu-Emil PrecupPolytechnic Univ. of Timisoara, Romania
Witold PedryczUniversity of Alberta, Canada
Araceli SanchisUniversity Carlos III, Madrid, Spain
Igor SkrjancUniversity of Ljubljana, Slovenia
Gancho VachkovSouth Pacific University, Fiji
Di WangKhalifa University, UAE
Ronald YagerIona College, NY, USA
Xiaojun ZengManchester University, UK