Call for Papers
28th International Workshop on
Evolutionary Rule-based Machine Learning
IWERL 2025 (formerly IWLCS)
to be held as part of GECCO (July 14 - 18, 2025) in Málaga,
Spain (online participation possible)
Modern machine learning systems offer significant
potential for addressing real-world challenges. However, the
decision-making process of the majority of these models is often
difficult to interpret. The interpretability of decisions is
critical in many real-world applications. Evolutionary
rule-based machine learning (ERL) systems generate niche-based
solutions, require less memory, and can be trained using
comparatively small data sets. The decision-making process of
the ERL systems is interpretable, which is an important step
toward eXplainable AI (XAI).
ERL methods have been developed using a diverse array of
learning paradigms, including supervised learning, unsupervised
learning, and reinforcement learning. ERL encompasses several
prominent categories, such as Learning Classifier Systems,
Ant-Miner, artificial immune systems, and fuzzy rule-based
systems. The International Workshop on Evolutionary Rule-based
Machine Learning (IWERL) is designed to provide a
platform for sharing the research trends in the realm of ERL. It
aims to highlight modern implementations of ERL
systems for real-world applications and to show the
effectiveness of ERL in creating flexible and eXplainable AI
systems. The particular topics of interest of this workshop are
(not exclusively):
-
Advances in ERL methods local
models, problem space partitioning, rule mixing, . . .
-
Applications of ERL medical
domains, bioinformatics, computer vision, games,
cyber-physical systems, . . .
-
State-of-the-art analysis surveys,
sound comparative experimental benchmarks, carefully crafted
reproducibility studies, . . .
-
Formal developments in ERL provably
optimal parametrization, time bounds, generalization, . . .
-
Comprehensibility of evolved rule
sets knowledge extraction, visualization,
interpretation of decisions, XAI, . . .
-
Advances in ERL paradigms Michigan/Pittsburgh
style, hybrids, iterative rule learning, . . .
-
Hyperparameter
optimization for ERL hyperparameter selection, online
self-adaptation, . . .
-
Optimizations and parallel
implementations GPU acceleration, matching
algorithms, . . .
-
Generative
AI and LLMs in ERL
Integration of generative models and LLMs with ERL, .
. .
Submission deadline: March 26, 2025
Decision notification: April 28, 2025
Camera-ready deadline: May 5, 2025
Why submit to IWERL ’25?
Submissions
Workshop organization
-
Abubakar Siddique, Wellington
Institute of Technology, New Zealand
-
Michael Heider, University of
Augsburg, Germany
-
Hiroki Shiraishi, Yokohama National
University, Japan