Aim and Scope

Evolutionary Machine Learning (EML) explores technologies that integrate machine learning (e.g., neural networks, decision trees, fuzzy systems, reinforcement learning) with evolutionary computation for tasks including optimization, classification, regression, and clustering. Since machine learning contributes to parameter learning while evolutionary computation contributes to model/parameter optimization, one of the fundamental interests in EML is a management of interactions between learning and evolution to produce a system performance that cannot be achieved by either of these approaches alone. Historically, this research area was called Genetics-Based Machine Learning (GBML) and it was concerned with learning classifier systems (LCS) with its numerous implementations. More recently, EML has emerged as a more general field than GBML. It is consequently a broader, more flexible and more capable paradigm than GBML. From this viewpoint, the aim of this special session is to explore potential EML technologies and clarify new directions for EML to show its prospects. For this purpose, this special session focuses on, but is not limited to, the following areas in EML:

- Evolutionary learning systems (e.g., learning classifier systems)

- Evolutionary neural network (e.g., neuroevolution, evolutionary deep neural networks)

- Evolutionary decision trees

- Evolutionary cascade systems

- Evolutionary fuzzy systems

- Evolutionary reinforcement learning

- Evolutionary ensemble systems

- Evolutionary adaptive systems

- Artificial immune systems

- Genetic programming applied to machine learning

- Evolutionary feature selection and construction for machine learning

- Transfer learning; learning blocks of knowledge (memes, code, etc.)

- Accuracy-interpretability tradeoff in EML

- Applications and theory of EML

This special session is the fifth edition of our previous special sessions in CEC2015, CEC2016, CEC2017, and CEC2018. The continuous exploration of this field by organizing the special session in CEC is indispensable to establish the discipline of EML.

This special session will be held in 2019 IEEE Congress on Evolutionary Computation (http://cec2019.org) (Wellington, New Zealand, June 10-13, 2019). All papers should be prepared according to the CEC 2019 policy. Please check the conference webpage. To submit your paper to this special session, you have to choose our special session on the submission page.