It is well known that incremental learning can often be difficult for traditional neural network systems, due to newly learned information interfering with previously learned infor...
The paper presents a framework called ECOS for Evolving COnnectionist Systems. ECOS evolve through incremental learning. They can accommodate any new input data, including new fea...
— A method is presented for extending the Evolving Connectionist System (ECoS) algorithm that allows it to explicitly represent and learn nominal-scale data without the need for ...
This paper investigates incremental multiagent learning in static or evolving structured networks. Learning examples are incrementally distributed among the agents, and the object...
Gauvain Bourgne, Amal El Fallah-Seghrouchni, Henry...
Abstract This paper depicts and evaluates an evolutionary design process for generating a complex self-organizing multicellular system based on Cellular Automata (CA). We extend th...