Data streams occur widely in various real world applications. The research on streaming data mainly focuses on the data management, query evaluation and optimization on these data, however the work on reasoning procedures for streaming knowledge bases on both the assertional and terminological levels is very limited. Typically reasoning services on large knowledge bases are very expensive, and need to be applied continuously when the data is received as a stream. Hence new techniques for optimizing this continuous process is needed for developing efficient reasoners on streaming data. In this paper, we survey the related research on reasoning on expressive logics that can be applied to this setting, and point to further research directions in this area.
Runtime commitment verification is an important, open issue in multiagent research. To address it, we build on Yolum and Singh's formalization of commitment operations, on Chittaro and Montanari's cached event calculus, and on the SCIFF abductive logic programming proof-procedure. We propose a framework consisting of a declarative and compact language to express the domain knowledge, and a reactive and complete procedure to track the status of commitments effectively, producing provably sound and irrevocable answers.
Only-knowing was originally introduced by Levesque to capture the beliefs of an agent in the sense that its knowledge base is all the agent knows. When a knowledge base contains defaults Levesque also showed an exact correspondence between only-knowing and autoepistemic logic. Later these results were extended by Lakemeyer and Levesque to also capture a variant of autoepistemic logic proposed by Konolige and Reiter's default logic. One of the benefits of such an approach is that various nonmonotonic formalisms can be compared within a single monotonic logic leading, among other things, to the first axiom system for default logic. In this paper, we will bring another large class of nonmonotonic systems, which were first studied by McDermott and Doyle, into the only-knowing fold. Among other things, we will provide the first possible-world semantics for such systems, providing a new perspective on the nature of modal approaches to nonmonotonic reasoning.
We investigate the problem of reasoning in the propositional fragment of MBNF, the logic of minimal belief and negation as failure introduced by Lifschitz, which can be considered as a unifying framework for several nonmonotonic formalisms, including default logic, autoepistemic logic, circumscription, epistemic queries, and logic programming. We characterize the complexity and provide algorithms for reasoning in propositional MBNF. In particular, we show that entailment in propositional MBNF lies at the third level of the polynomial hierarchy, hence it is harder than reasoning in all the above mentioned propositional formalisms for nonmonotonic reasoning. We also prove the exact correspondence between negation as failure in MBNF and negative introspection in Moore's autoepistemic logic.