Title :
Evolving connectionist systems for adaptive learning and knowledge discovery: methods, tools, applications
Author_Institution :
Knowledge Eng. & Discovery Res. Inst., Auckland Univ. of Technol., New Zealand
Abstract :
The paper describes what evolving processes are and presents a computational model called evolving connectionist systems (ECOS). The model is based on principles from both brain organization and genetics. The applicability of the model for dynamic modeling and knowledge discovery in the areas of brain study, bioinformatics, speech and language learning, adaptive control and adaptive decision support is discussed.
Keywords :
adaptive systems; data mining; decision support systems; neural nets; physiological models; adaptive decision support system; adaptive learning; bioinformatics; brain organization; evolving connectionist systems; genetics; knowledge discovery; neural network; Adaptive control; Adaptive systems; Bioinformatics; Biological neural networks; Brain modeling; DNA; Information processing; Natural languages; Neurons; RNA;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1198126
