2005/01/01 by Yi Jin, Jin, Yi, Michael Thielscher +1
Computer Science · #Bayesian Modeling and Causal Inference #Belief Base Revision #Computational Complexity #Iterated Belief Revision #Logic, Reasoning, and Knowledge #Multi-Agent Systems and Negotiation
paper · doi:10.4230/dagsemproc.05321.5
openalex publication_date 2005/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The classic AGM theory studies mathematically idealized models of belief revision in two aspects: the properties (i.e., the AGM postulates) a rational revision operator should satisfy; and how to mathematically construct concrete revision operators. In scenarios where new information arrives in sequence, rational revision operators should also respect postulates for iterated revision (e.g., the DP postulates). When applications are concerned, the idealization of the AGM theory has to be lifted, in particular, beliefs of an agent should be represented by a finite belief base. In this talk, we present a computational base revision operator, which satisfies the AGM postulates and some nice postulates for iterated revision. We will also give a formal assessment of the base revision operator in terms of its computational complexity and degree of syntax irrelevance.