Knowledge Granularity Spectrum, Action Pyramid, and the Scaling Problem

In this paper we introduce the concept of knowledge granularity and study the relationship between different knowledge representation schemes and the scaling problem. By scale to a task, we mean that an agent's planning system and knowledge representation scheme are able to generate the range of behaviors required by the task in a timely fashion. Action selection is critical to an agent performing a task in a dynamic, unpredictable environment. Knowledge representation is central to the agent's action selection process. It is important to study how an agent should adapt its methods of representation such that its performance can scale to different task requirements. Here we study the following issues. One is the knowledge granularity problem: to what detail should an agent represent a certain kind of knowledge if a single granularity of representation is to be used. Another is the representation scheme problem: to scale to a given task, should an agent represent its knowledge using a single granularity or a set of hierarchical granularities.

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