Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
An extended fuzzy linguistic approach to generalize Boolean information retrieval
Information Sciences—Applications: An International Journal
Communications of the ACM
Soft Computing and Fuzzy Logic
IEEE Software
Software Agents and Soft Computing: Towards Enhancing Machine Intelligence, Concepts and Applications
Handling uncertainty in finance applications using soft computing
ISUMA '95 Proceedings of the 3rd International Symposium on Uncertainty Modelling and Analysis
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BT Technology Journal
Adaptive User Modelling in an Intelligent Telephone Assistant
Soft-Ware 2002 Proceedings of the First International Conference on Computing in an Imperfect World
No Pervasive Computing without Intelligent Systems
BT Technology Journal
A Profile Modelling Approach for E-Learning Systems
ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II
Development of an intelligent customised service system for contact centres
DNCOCO'06 Proceedings of the 5th WSEAS international conference on Data networks, communications and computers
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This paper considers the abstract features of human/machine interaction systems that are required for the production of intelligent behaviour. A conceptual architecture is then proposed for a subset of intelligent systems called human-centred intelligent systems (HCISs) and it is argued that such systems must be autonomous, robust and adaptive in order to be intelligent. Soft computing is proposed as a promising new technique that can be used to build HCISs, and examples are presented where this is already being done. Finally, flexibility is defined to be a combination of the often-conflicting requirements of robustness and adaptability, and it is argued that the right balance between these two features is necessary to achieve intelligent behaviour.