Concept Formation

Concept formation research investigates how systems, both artificial and biological, acquire and organize knowledge into meaningful categories or concepts. Current research focuses on developing and evaluating algorithms, including those based on hierarchical clustering, language models, and adaptations of human-inspired incremental learning systems like Cobweb, to improve concept representation and learning efficiency in various domains, such as image recognition and e-commerce. These advancements are significant for improving the explainability and robustness of AI systems, as well as for furthering our understanding of human cognition and knowledge representation.