Refinement Quantified Logics of Knowledge and Belief for Multiple Agentsc
نویسندگان
چکیده
Given the “possible worlds” interpretation of modal logic, a refinement of a Kripke model is another Kripke model in which an agent has ruled out some possible worlds to be consistent with some new information. The refinements of a finite Kripke model have been shown to correspond to the results of applying arbitrary action models to the Kripke model [10]. Refinement modal logics add quantifiers over such refinements to existing modal logics. Work by van Ditmarsch, French and Pinchinat [11] gave an axiomatisation for the refinement modal logic over the class of unrestricted Kripke models, for a single agent. Recent work by Hales, French and Davies [13] extended these results, restricting the quantification to the class of doxastic and epistemic models for a single agent. Here we extend these results further, to the classes of doxastic and epistemic models for multiple agents. The generalisation to multiple agents for doxastic and epistemic models is not straightforward and requires novel techniques, particularly for the epistemic case. We provide sound and complete axiomatisations for the considered logics, and a provably correct translations to their underlying modal logics, corollaries of which are expressivity and decidability results.
منابع مشابه
A Resolution Method for Quantified Modal Logics of Knowledge and Belief
B-resolution is a sound and complete resolution rule for quantified modal logics of knowledge and belief with a standard Kripke semantics. It differs from ordinary first-order binary resolution in that it can have an arbitrary (but finite) number of inputs, is not necessarily effective, and does not have a most general unifier covering every instance of an application. These properties present ...
متن کاملKnowledge Base Revision in Description Logics
Ontology evolution is an important problem in the Semantic Web research. Recently, Alchourrón, Gärdenfors and Markinson’s (AGM) theory on belief change has been applied to deal with this problem. However, most of current work only focuses on the feasibility of the application of AGM postulates on contraction to description logics (DLs), a family of ontology languages. So the explicit constructi...
متن کاملbelief function and the transferable belief model
Beliefs are the result of uncertainty. Sometimes uncertainty is because of a random process and sometimes the result of lack of information. In the past, the only solution in situations of uncertainty has been the probability theory. But the past few decades, various theories of other variables and systems are put forward for the systems with no adequate and accurate information. One of these a...
متن کاملConsidering Uncertainty in Modeling Historical Knowledge
Simplifying and structuring qualitatively complex knowledge, quantifying it in a certain way to make it reusable and easily accessible are all aspects that are not new to historians. Computer science is currently approaching a solution to some of these problems, or at least making it easier to work with historical data. In this paper, we propose a historical knowledge representation model takin...
متن کاملReasoning about Knowledge and Belief
An agent operating in a complex environment can benefit from adapting its behavior to the situation at hand. The agent's choice of actions at any point in time can, however , be based only on its local knowledge and beliefs. When many agents are present, the success of one's agent's actions will typically depend on the actions of the other agents. These, in turn, are based on the other agents' ...
متن کامل