Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
International Journal of Man-Machine Studies - Special issue: symbolic problem solving in noisy and novel task environments
Machine Learning
Machine Learning
The logic of “initially” and “next”: complete axiomatization and complexity
Information Processing Letters
Machine Learning
A Conceptual Graph Model for W3C Resource Description Framework
ICCS '00 Proceedings of the Linguistic on Conceptual Structures: Logical Linguistic, and Computational Issues
Learning Collective Behaviour from Local Interactions
CEEMAS '01 Revised Papers from the Second International Workshop of Central and Eastern Europe on Multi-Agent Systems: From Theory to Practice in Multi-Agent Systems
CPlanT: An Acquaintance Model-Based Coalition Formation Multi-agent System
CEEMAS '01 Revised Papers from the Second International Workshop of Central and Eastern Europe on Multi-Agent Systems: From Theory to Practice in Multi-Agent Systems
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We present in this paper some attempts to design a Machine Learning method to predict preference knowledge in a multi-agents context. This approach is applied to a corporate knowledge management system.