Iterated belief revision, revised

The AGM postulates for belief revision, augmented by the DP postulates for iterated belief revision, provide generally accepted criteria for the design of operators by which intelligent agents adapt their beliefs incrementally to new information. These postulates alone, however, are too permissive: They support operators by which all newly acquired information is canceled as soon as an agent learns a fact that contradicts some of its current beliefs. In this paper, we present a formal analysis of the deficiency of the DP postulates, and we show how to solve the problem by an additional postulate of independence. We give a representation theorem for this postulate and prove that it is compatible with AGM and DP.

• Type: Journal
• Year: 2007
• Where: AI
• Authors: Yi Jin, Michael Thielscher
• Keywords: AI 2007, Artificial Intelligence, Belief Revision, Intelligent Agents, Operators