The Special Session on Evolutionary Machine Learning (EML) of Evo Apps will provide a specialized forum of discussion and exchange of information for researchers interested in exploring approaches that combine nature and nurture, with the long-term goal of evolving Artificial Intelligence (AI).

Giving response to the growing interest in the area, and consequent advances of the state-of-the-art, the special session covers theoretical and practical advances on the combination of Evolutionary Computation (EC) and Machine Learning (ML) techniques.

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Topics of Interest

Topics of interest include, but are not limited to:

  • EC as an ML technique: Using EC to solve typical ML tasks such as Classification or Clustering
  • EC applied ML algorithms: Neuroevolution, Feature Selection, Feature Engineering, Evolutionary Adversarial Models
  • ML applied to EC: Surrogate-model design by ML for EC, Learning Problem Structure, ML for Diversity, Designing Search Strategies, Predicting Promising Regions, Using ML to Decrease Computational Effort
  • Real world applications issues: EC for Fairness, Robustness, Trustworthiness and Explainability; Green EML
  • Emerging topics: EC for AutoML; EC for Transfer Learning; EC for Multitasking; Evolving Learning Functions, Neurons and Linkage; EC for Verification and Validation of ML

Download the EvoAPPS special session on EML flyer

Submission Details

Submissions must be original and not published elsewhere. They will be peer reviewed by members of the program committee. The reviewing process will be double-blind, so please omit information about the authors in the submitted paper. 

Submit your manuscript in Springer LNCS format and provide up to five keywords in your Abstract

Page limit: 16 pages
Submission link:


Penousal Machado
Wolfgang Banzhaf