Artificial Dasein: Solving the Frame Problem with Incremental Contextualization

Abstract

In this paper, we give an account of a rationally behaving agent-an artificial Dasein-which can perceive the world in terms of relevance to its own goals.The way we achieve this is through a process of incremental contextualization of goals and constraints that range from the purely conceptual and abstract to the well-defined and physical. The model described in this paper combines a conceptual hierarchy with a schema structure, and leads to an account of practical reasoning which relies on two novel ideas: the recursive selection of increasingly contextualized subgoals, and the tractable determination of behavioral consequences through simulation. The present account seeks to provide an outline for developing an agent which does not suffer from the frame problem due to the way in which it incrementally contextualizes its goals until they can be achieved unreflectively by matching them to pre-learned schemas. We believe that this account can lead to a form of artificial intelligence more powerful than traditional attempts based on formal logic.