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<p><b>Abstract</b>—A probabilistic network consists of a dependency structure and corresponding probability tables. The <it>dependency structure</it> is a graphical representation of the conditional independencies that are known to hold in the problem domain. In this paper, we propose an automated process for constructing the combined dependency structure of a <it>multiagent</it> probabilistic network. Each domain expert supplies any known conditional independency information and not necessarily an explicit dependency structure. Our method determines a succinct representation of all the supplied independency information called a <it>minimal cover</it>. This process involves detecting all <it>inconsistent</it> information and removing all <it>redundant</it> information. A <it>unique</it> dependency structure of the multiagent probabilistic network can be constructed directly from this minimal cover. The main result of this paper is that the constructed dependency structure is a <it>perfect-map</it> of the minimal cover. That is, every probabilistic conditional independency logically implied by the minimal cover can be inferred from the dependency structure and every probabilistic conditional independency inferred from the dependency structure is logically implied by the minimal cover.</p>
Probabilistic networks, dependency structure, probabilistic reasoning, conditional independence, data dependencies, multiagent systems.

S. M. Wong and C. J. Butz, "Constructing the Dependency Structure of a Multiagent Probabilistic Network," in IEEE Transactions on Knowledge & Data Engineering, vol. 13, no. , pp. 395-415, 2001.
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