Titlebook: Artificial Intelligence Applications and Innovations; IFIP 18th World Comp Max Bramer,Vladan Devedzic Conference proceedings 2004 IFIP Inte

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Licentious

Verification of NASA Emergent Systemsano Technology Swarm) mission, will comprise of 1,000 autonomous robotic agents designed to cooperate in asteroid exploration. The emergent properties of swarm type missions make them powerful, but at the same time are more difficult to design and assure that the proper behaviors will emerge. We are

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SYN

Learning Bayesian Metanetworks from Data with Multilevel Uncertainty managing context in Bayesian networks are the introduction of contextual (in)dependence and Bayesian multinets. We are presenting one possible implementation of a context sensitive Bayesian multinet-the Bayesian Metanetwork, which implies that interoperability between component Bayesian networks (v

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Efficient Attribute Reduction Algorithmms. However, some of its algorithms’ consuming time limits the applications of rough set. According to this, our paper analyzes the reasons of rough set algorithms’ inefficiency by focusing on two important factors: indiscernible relation and positive region, and analyzes an equivalent and efficient

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随意

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Learning Bayesian Metanetworks from Data with Multilevel Uncertaintyalid in different contexts) can be also modelled by another Bayesian network. The general concepts and two kinds of such Metanetwork models are considered. The main focus of this paper is learning procedure for Bayesian Metanetworks.