Introduction to Bayesian Networks
Introduction to Bayesian Networks
Knowledge Management: Problems, Promises, Realities, and Challenges
IEEE Intelligent Systems
Simulation Approaches to General Probabilistic Inference on Belief Networks
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Modeling Corporate Knowledge within the Agent Oriented Abstraction
CW '04 Proceedings of the 2004 International Conference on Cyberworlds
Corporate Knowledge in Cyberworlds*
IEICE - Transactions on Information and Systems
OntoBayes: An Ontology-Driven Uncertainty Model
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06) - Volume 01
Virtual knowledge communities for corporate knowledge issues
ESAW'04 Proceedings of the 5th international conference on Engineering Societies in the Agents World
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In this paper, we investigate the integration of virtual knowledge communities (VKC) into an ontology-driven uncertainty model (OntoBayes). The selected overall framework for OntoBayes is the multiagent paradigm. Agents modeled with OntoBayes have two parts: knowledge and decision making parts. The former is the ontology knowledge while the latter is based upon Bayesian Networks (BN). OntoBayes is thus designed in agreement with the Agent Oriented Abstraction (AOA) paradigm. Agents modeled with OntoBayes possess a common community layer that enables to define, describe and implement corporate knowledge. This layer consists of virtual knowledge communities.