Uncertainty Characterization and Fusion of Information from Unreliable Sources

Abstract

Intelligent systems collect information from various sources to support their decision-making. However, misleading information may lead to wrong decisions with significant losses. Therefore, it is crucial to develop mechanisms that will make such systems immune to misleading information. This chapter presents a framework to exploit reports from possibly unreliable sources to generate fused information, i.e., an estimate of the ground truth, and characterize the uncertainty of that estimate as a facet of the quality of the information. First, the basic mechanisms to estimate the reliability of the sources and appropriately fuse the information are reviewed when using personal observations of the decision-maker and known types of source behaviors. Then, we propose new mechanisms for the decision-maker to establish fused information and its quality when it does not have personal observations and knowledge about source behaviors.