1. Learning Classifier Systems
They are rule-based, multifaceted, machine learning algorithms originated and have evolved in the cradle of evolutionary biology and artificial intelligence. The LCS concept has inspired a multitude of implementations adapted to manage the different problem domains to which it has been applied (e.g., autonomous robotics, classification, knowledge discovery, and modeling). One field that is taking increasing notice of LCS is epidemiology, where there is a growing demand for powerful tools to facilitate etiological discovery. Unfortunately, implementation optimization is nontrivial, and a cohesive encapsulation of implementation alternatives seems to be lacking.
1 Ryan J. Urbanowicz and Jason H. Moore, “Learning Classifier Systems: A Complete Introduction, Review, and Roadmap,” Journal of Artificial Evolution and Applications, vol. 2009, Article ID , 25 pages, doi: /2009/736398 2.