Planning under continuous time and resource uncertainty: A challenge for AI

Planning under continuous time and resource uncertainty: A challenge for AI (2002)

by John Bresina , Nicolas Meuleauy , Sailesh Ramakrishnan , David Smith , Rich Washingtonx

Venue:	In Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence
Citations:	81 - 13 self

Datum	Value	Source
TITLE	Planning under continuous time and resource uncertainty: A challenge for AI	INFERENCE
AUTHOR NAME	John Bresina	SVM HeaderParse 0.2
AUTHOR AFFIL	NASA Ames Research CenterMail stop 269-2	SVM HeaderParse 0.2
AUTHOR ADDR	Moffet Field, CA 94035-1000, USA	SVM HeaderParse 0.2
AUTHOR NAME	Nicolas Meuleauy	SVM HeaderParse 0.2
AUTHOR NAME	Sailesh Ramakrishnan	SVM HeaderParse 0.2
AUTHOR NAME	David Smith	SVM HeaderParse 0.2
AUTHOR NAME	Rich Washingtonx	SVM HeaderParse 0.2
AUTHOR AFFIL	\Lambda Research Institute for Advanced Computer Science (RIACS)	SVM HeaderParse 0.2
ABSTRACT	yQSS Group Inc. zQSS Group Inc. xRIACS experiment is assigned a scientific value). Different ob-servations and experiments take differing amounts of time and consume differing amounts of power and data storage.There are, in general, a number of constraints that govern the rovers activities: ffl There are time, power, data storage, and posi-tioning constraints for performing different activities. Time constraints often result from illuminationrequirement--that is, experiments may require that a target rock or sample be illuminated with a certain in-tensity, or from a certain angle.	SVM HeaderParse 0.2
YEAR	2002	INFERENCE
VENUE	In Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	77--84	INFERENCE
CITATIONS	17 found	ParsCit 1.0