From knowledge-based programs to graded belief-based programs - Part I: on-line reasoning
Noël Laverny, Jérôme Lang · European Conference on Artificial Intelligence · 2004
Knowledge-based programs ([10, 18]) are a powerful notion for expressing action policies in which branching conditions refer to implicit knowledge. However, branching conditions in knowledge-based programs cannot refer to possibly erroneous beliefs or to graded belief, such as if my belief that φ holds is high then do some action α else perform some sensing action β. The purpose of this paper is to build a framework where such programs can be expressed. In this paper we focus on the execution of such a program (a companion paper investigates issues relevant to the off-line evaluation and construction of such programs). We define a simple graded version of doxastic logic KD45 as the basis for the definition of belief-based programs. Then we study the way the agent's belief state is maintained when executing such programs, which calls for revising belief states by observations (possibly unreliable or imprecise) and progressing belief states by physical actions (which may have normal as well as exceptional effects).