============ *Call for Papers* ============ *29th International Workshop on Evolutionary Rule-based Machine Learning IWERL 2026* (formerly IWLCS) to be held as part of GECCO (July 13 - 17, 2026) in San José, Costa Rica (online participation possible) Modern machine learning systems, including generative AI and large language models, 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 27, 2026* Decision notification: April 24, 2026 Camera-ready deadline: May 5, 2026 Author's mandatory registration: May 11, 2026 * Why submit to IWERL ’26?* * reviews by renowned ERL experts * published as part of the GECCO conference companion * usually online within one month after the conference *Submissions* * This workshop accepts two types of submissions: o research papers on novel findings or improvements o position papers making a concise argument based on preliminary findings * All submissions must conform to the GECCO submission instructions (https://gecco-2026.sigevo.org/Paper-Submission-Instructions) and be submitted via GECCO’s submission system (https://ssl.linklings.net/conferences/gecco/). * In 2026, you can submit either 8 pages (excl. references) with APC or 4 pages (incl. references) without APC. *Workshop organization* * Michael Heider, University of Augsburg, Germany * Hiroki Shiraishi, Yokohama National University, Japan * Fumito Uwano, Okayama University, Japan * Connor Schönberner, Kiel University, Germany More information can be found at*https://iwlcs.organic-computing.de*