Fred meets Tweety

We propose a framework that brings together two major forms of default reasoning in Artificial Intelligence: applying default property classification rules in static domains, and default persistence of properties in temporal domains. Particular attention is paid to the problem of qualification, central in default reasoning and in any attempt to integrate different forms of this type of reasoning. We examine previous semantics developed independently for the two separate forms of default reasoning, and illustrate how these naturally lead to the solution that we propose in integrating the two. The resulting integration gives rise to domains where four different types of knowledge interact and qualify each other in an intricate manner. Through a series of examples we show how this knowledge qualification leads to intuitive conclusions. We prove that our framework of integration is elaboration tolerant: extending a consistent domain with additional action occurrences, causal laws, or static knowledge does not render the domain inconsistent. The conclusions that are drawn are always adjusted so as to gracefully accommodate the extra knowledge.