On the knowledge requirements of tasks

作者:

摘要

In order to successfully perform a task, a situated system requires some information about its domain. If we can understand what information the system requires, we may be able to equip it with more suitable sensors or make better use of the information available to it. These considerations have motivated roboticists to examine the issue of sensor design, and in particular, the minimal information required to perform a task. We show here that reasoning in terms of what the robot knows and needs to know to perform a task is a useful approach for analyzing these issues. We extend the formal framework for reasoning about knowledge, already used in AI and distributed computing, by developing a set of basic concepts and tools for modeling and analyzing the knowledge requirements of tasks. We investigate properties of the resulting framework, and show how it can be applied to robotics tasks.

论文关键词:Knowledge,Sensor design,Configuration space,Manipulation tasks,(Skeletal) knowledge-based programs,Knowledge complexity,Knowledge capability

论文评审过程:Available online 23 June 1998.

论文官网地址:https://doi.org/10.1016/S0004-3702(97)00061-1