A Unified View of Consequence Relation, Belief Revision, and Conditional Logic *
Hirofumi Katsuno, Ken Satoh · 1995
Abstract The notion of minimality is proving to be a key unifying idea in three different areas of Artificial Intelligence: non-monotonic reasoning, belief revision, and conditional reasoning. However, it is difficult for the readers of the literature in these areas to perceive the similarities clearly. The models used in each area differ, sometimes superficially and sometimes in depth, and the notation is different. This makes it hard to apply results on, say, conditional logic to, say, belief revision. Even within the same area there is confusion, as, for example, different authors use different formalisms for conditional logic, sometimes without relating their proposals to the literature. We therefore present a uniform view of how minimality is used in these three areas, shedding light on deep connections among the areas. We clarify differences and similarities between different approaches by classifying them according to the notion of minimality on which they are based.