Mathematics of Data Fusion
Multiagent Collaborative Learning for Distributed Business Systems
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Infrastructural Issues for Agent-Based Distributed Learning
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
A Meta-ontological Framework for Multi-agent Systems Design
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
DPMF: A policy management framework for heterogeneous authorization systems in grid environments
Multiagent and Grid Systems - Content management and delivery through P2P-based content networks
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Integration of the multi-agent and data mining technologies is one of the noticeable trends in the modern information technology. This integration contributes to the further progress in both above areas and provides practitioners with a new kind of technology of distributed intelligent systems. However, this integration generates a number of new non-typical problems both in areas, data mining and multi-agent systems. This fact is explicitly confirmed by the tasks of multi-agent distributed learning where new problems are mostly caused by the fact that data mining and learning procedures are always interactive and if learning data are distributed and private then multiple humans supported by distributed software should be involved in these procedures. Therefore, special means are needed to coordinate their activities in order to achieve consistency and integrity of the final solutions. The paper considers one of the key problems of the multi-agent distributed learning: development of the distributed classification systems' ontology. The paper analyzes the basic aspects of this weakly studied though important and challenging problem and proposes several solutions capable to constitute a basis for ontology design technology as applied to distributed data mining, learning and classification.