A logic for reasoning about evidence and belief

In agent-based systems, an agent generally forms her belief based on evidence from multiple sources, such as messages from other agents or perception of the external environment. In this paper, we present a logic for reasoning about evidence and belief. Our framework not only takes advantage of the source-tracking capability of justification logic, but also allows the distinction between the actual observation and simply potential admissibility of evidence. We present the axiomatization for the basic logic and its dynamic extension, investigate its properties, and use a running example to show its applicability to information fusion for autonomous agents.