Learning with adaptivity is a key issue in many nowadays applications. The most important 
aspect of such an issue is incremental learning (IL). This latter seeks to equip learning 
algorithms with the ability to deal with data arriving over long periods of time. Once used 
during the learning process, old data is never used in subsequent learning stages. 
This paper suggests a new algorithm to deal with IL. It consists of generating prototyped 
categories which are linked to classes. They are incrementally created and dynamically 
controlled. To exhibit the behavior of the algorithm, an empirical evaluation is carried out.