Dynamic Logic of Trust-Based Beliefs
By: Junli Jiang, Pavel Naumov, Wenxuan Zhang
Potential Business Impact:
Helps computers learn from new information shared publicly.
Traditionally, an agent's beliefs would come from what the agent can see, hear, or sense. In the modern world, beliefs are often based on the data available to the agents. In this work, we investigate a dynamic logic of such beliefs that incorporates public announcements of data. The main technical contribution is a sound and complete axiomatisation of the interplay between data-informed beliefs and data announcement modalities. We also describe a non-trivial polynomial model checking algorithm for this logical system.
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