AGM-Style Revision of Beliefs and Intentions from a Database Perspective (Preliminary Version)
This work addresses a foundational issue in AI and logic for formalizing belief and intention revision, but it appears incremental as it builds on existing AGM and database perspectives.
The paper tackles the problem of revising beliefs and intentions in a temporal logic framework by introducing a separation between strong and weak beliefs and formalizing coherence conditions. It provides AGM-style postulates for revision and proves a representation theorem linking these postulates to a pre-order on interpretations and a selection function.
We introduce a logic for temporal beliefs and intentions based on Shoham's database perspective. We separate strong beliefs from weak beliefs. Strong beliefs are independent from intentions, while weak beliefs are obtained by adding intentions to strong beliefs and everything that follows from that. We formalize coherence conditions on strong beliefs and intentions. We provide AGM-style postulates for the revision of strong beliefs and intentions. We show in a representation theorem that a revision operator satisfying our postulates can be represented by a pre-order on interpretations of the beliefs, together with a selection function for the intentions.