With agents relying more and more on information from central servers rather than their own sensors, knowledge becomes property not of a specific agent but of the data that the agents can access. The article proposes a dynamic logic of data-informed knowledge that describes an interplay between three modalities and one relation capturing the properties of this form of knowledge. The main technical results are the undefinability of two dynamic operators through each other, a sound and complete axiomatisation, and a (...) model checking algorithm. (shrink)

If an agent prefers one kind of agents to the other agents, then the agent has first-order preferences. If the agent prefers agents with one kind of preferences to the other agents, then the agent has second-order preferences. The article proposes a sound, complete, and decidable logical system capable of expressing higher-order preferences.

Traditionally, knowledge and beliefs are attributed to agents. The article explores an alternative approach where knowledge is informed by data and belief comes from trust in, not necessarily reliable, data. At the core of the article is the modality “if one dataset is trusted, then another dataset informs a belief”. The main technical result is a sound and complete logical system capturing the properties of this modality and its connection with functional dependency between datasets.