Omnipotence Without Omniscience: Efficient Sensor Management for Planning

Abstract

Classical planners have traditionally made the closed world assumption --- facts absent from the planner's world model are false. Incompleteinformation 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. Introduction Classical planners (e.g., (Chapman 1987)) presuppose correct and complete information about the world. Although recent wo...

Cite

Text

Golden et al. "Omnipotence Without Omniscience: Efficient Sensor Management for Planning." AAAI Conference on Artificial Intelligence, 1994.

Markdown

[Golden et al. "Omnipotence Without Omniscience: Efficient Sensor Management for Planning." AAAI Conference on Artificial Intelligence, 1994.](https://mlanthology.org/aaai/1994/golden1994aaai-omnipotence/)

BibTeX

@inproceedings{golden1994aaai-omnipotence,
  title     = {{Omnipotence Without Omniscience: Efficient Sensor Management for Planning}},
  author    = {Golden, Keith and Etzioni, Oren and Weld, Daniel S.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1994},
  pages     = {1048-1054},
  url       = {https://mlanthology.org/aaai/1994/golden1994aaai-omnipotence/}
}