Fusion Techniques for Reliable Information: A Survey <s> Modal Logic (ML) & Knowledge Logic (KL) <s> From the Publisher: ::: This invaluable reference offers the most comprehensive introduction available to the concepts of multisensor data fusion. It introduces key algorithms, provides advice on their utilization, and raises issues associated with their implementation. With a diverse set of mathematical and heuristic techniques for combining data from multiple sources, the book shows how to implement a data fusion system, describes the process for algorithm selection, functional architectures and requirements for ancillary software, and illustrates man-machine interface requirements an database issues. <s> BIB001 </s> Fusion Techniques for Reliable Information: A Survey <s> Modal Logic (ML) & Knowledge Logic (KL) <s> Information fusion is the process of deriving a single consistent knowledgebase from multiple knowledgebases. This process is important in many cognitive tasks such as decision-making, planning, design, and specification, that can involve collecting information from a number of potentially conflicting perspectives or sources, or participants. In this brief overview, we focus on the problem of inconsistencies arising in information fusion. In the following, we consider reasoning with inconsistencies, acting on inconsistencies, and resolving inconsistencies. <s> BIB002
ML is any system of formal logic that attempts to treat modalities (e.g., possibility, probability, and necessity). A formal ML represents modalities using a modal operator. The basic modal operators are usually written L for "Necessity" and M for "Possibility" BIB002 . In addition, KL is a logical definition in multi-modal logic systems. KL is a special kind of knowledge for group agents. KL represents the state of knowledge of the agent in given state using set theory BIB001 . However, it is difficult to define how many modalities are used in the same situation and new modalities may arise in the middle of a decision support task.