Dynamic Awareness
This work addresses a theoretical problem in AI and decision-making for researchers, but it is incremental as it builds directly on prior work.
The paper tackles the problem of modeling an agent's beliefs as they become aware of new information, extending an existing framework by incorporating probability and defining model transitions for awareness acquisition, and applies this model to information disclosure scenarios.
We investigate how to model the beliefs of an agent who becomes more aware. We use the framework of Halpern and Rego (2013) by adding probability, and define a notion of a model transition that describes constraints on how, if an agent becomes aware of a new formula $φ$ in state $s$ of a model $M$, she transitions to state $s^*$ in a model $M^*$. We then discuss how such a model can be applied to information disclosure.