Title :
Evolving connectionist systems for adaptive learning and knowledge discovery: Methods, tools, applications
Author_Institution :
Knowledge Eng. & Discovery Res. Inst., Atickland Univ. of Technol., Auckland, 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 control; data mining; learning (artificial intelligence); neural nets; adaptive control; adaptive decision support; adaptive learning; bioinformatics; brain organization; computational model; connectionist systems; dynamic modeling; evolving connectionist system; genetics; knowledge discovery; language learning; speech; Adaptive control; Adaptive systems; Biological neural networks; Brain modeling; DNA; Information processing; Natural languages; Neurons; RNA; Speech;
Conference_Titel :
Intelligent Systems, 2002. Proceedings. 2002 First International IEEE Symposium
Print_ISBN :
0-7803-7134-8
DOI :
10.1109/IS.2002.1044223
