5 research outputs found

    An Improved Belief Entropy and Its Application in Decision-Making

    Get PDF

    A belief revision framework for revising epistemic states with partial epistemic states

    Get PDF
    Belief revision performs belief change on an agent’s beliefs when new evidence (either of the form of a propositional formula or of the form of a total pre-order on a set of in-terpretations) is received. Jeffrey’s rule is commonly used for revising probabilistic epistemic states when new informa-tion is probabilistically uncertain. In this paper, we propose a general epistemic revision framework where new evidence is of the form of a partial epistemic state. Our framework extends Jeffrey’s rule with uncertain inputs and covers well-known existing frameworks such as ordinal conditional func-tion (OCF) or possibility theory. We then define a set of pos-tulates that such revision operators shall satisfy and establish representation theorems to characterize those postulates. We show that these postulates reveal common characteristics of various existing revision strategies and are satisfied by OCF conditionalization, Jeffrey’s rule of conditioning and possi-bility conditionalization. Furthermore, when reducing to the belief revision situation, our postulates can induce most of Darwiche and Pearl’s postulates
    corecore