About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
Artificial Intelligence
Paper
A logic to reason about likelihood
Abstract
We present a logic LL which uses a modal operator L to help capture the notion of being likely. Despite the fact that likelihood is not assigned quantitative values through probabilities, LL captures many of the properties of likelihood in an intuitively appealing way. We give a possible-worlds style semantics to LL, and, using standard techniques of modal logic, we give a complete axiomatization for LL and show that satisfiability of LL formulas can be decided in exponential time. We discuss how the logic might be used in areas such as medical diagnosis, where decision making in the face of uncertainties is crucial. We conclude by using LL to give a formal proof of correctness of some aspects of a protocol for exchanging secrets. © 1987.