The goal of this Committee (eIS) is to develop novel online learning methods and computationally efficient algorithms for real-time applications leading to evolvable classifiers, predictors, controllers, decision trees, fuzzy systems, neural networks. Cognitive and psychological aspects of the evolution of individual systems will also be of interest.
Handbook on Computational Intelligence published (World Scientific, 2016, 2 volumes)
Advances in Computational Intelligence Systems (Springer, 2016)
Advances in Big Data (Springer, 2017)
We welcome anyone who is interested in Evolving Intelligent Systems field to join us. If you would like to join, please contact the TC Chair.