Omnipotence Without Omniscience: Efficient Sensor Management for Planning
Omnipotence Without Omniscience: Efficient Sensor Management for Planning
复制标题
没有全知的全能：用于规划的高效传感器管理
DOI：
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发表时间：
1994
期刊：
影响因子：
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通讯作者：
Daniel S. Weld
中科院分区：
文献类型：
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作者：
K. Golden;Oren Etzioni;Daniel S. Weld
传统的规划师传统上做出了封闭世界的假设--规划师的世界模型中没有的事实是错误的。不完全信息规划者做出开放世界假设--规划者模型中不存在的事实的真值是未知的，必须被感知。开放世界假设导致了两个困难：（1）计划者如何确定一个普遍量化目标的范围？(2)什么时候一个感觉动作是多余的，产生的信息已经为计划者所知？
本文介绍了完全实现的XII计划，它解决了这两个问题，通过表示和推理当地的封闭世界信息（LCW）。我们报告的实验，利用我们的UNIX软机器人（软件机器人），这表明LCW可以大大提高软机器人的性能，消除冗余信息收集。
Classical planners have traditionally made the closed world assumption — facts absent from the planner's world model are false. Incomplete-information planners make the open world assumption — the truth value of a fact absent from the planner's model is unknown, and must be sensed. The open world assumption leads to two difficulties: (1) How can the planner determine the scope of a universally quantified goal? (2) When is a sensory action redundant, yielding information already known to the planner?
This paper describes the fully-implemented XII planner, which solves both problems by representing and reasoning about local closed world information (LCW). We report on experiments utilizing our UNIX softbot (software robot) which demonstrate that LCW can substantially improve the softbot's performance by eliminating redundant information gathering.