DocumentCode :
1112281
Title :
AI-based planning for data analysis
Author :
Lansky, Amy L. ; Philpot, Andrew G.
Author_Institution :
Artificial Intelligence Res. Branch, NASA Ames Res. Center, Moffett Field, CA, USA
Volume :
9
Issue :
1
fYear :
1994
Firstpage :
21
Lastpage :
27
Abstract :
Over the next 10 years (1994-2004), NASA plans to launch several satellites for studying Earth´s ecosystems. This Earth Observing System is expected to provide about a terabyte of data per day. The authors have worked with Earth scientists at NASA Ames to encode the selection and preparation of this data as an AI-based planning task. They extended a domain independent planner called Collage, to meet the requirements of this domain, and are building a prototype application that selects and prepares data for ecosystem models. Collage is a successor to the Gemplan planner. Both systems were designed for large, complex planning domains and have been applied to standard toy problems as well as more realistic domains, such as building-construction planning. Two features distinguish Collage from other domain-independent planners. First, instead of state-based planning algorithms, Collage uses a broad repertoire of domain independent, action-based plan-construction algorithms. It can also be extended to include new planning methods, including domain-specific ones. Second, Collage uses localized search: using information about domain structure, the planner partitions a potentially intractable, global search space into smaller, more manageable ones, each working on a local subproblem of the overall task.<>
Keywords :
data acquisition; data analysis; ecology; geophysics computing; knowledge based systems; planning (artificial intelligence); AI-based planning; AI-based planning task; Collage; Earth Observing System; Earth ecosystems; Gemplan planner; NASA; action-based plan-construction algorithms; complex planning domains; data analysis; domain independent planner; domain structure; domain-independent planners; ecosystem models; global search space; local subproblem; localized search; prototype application; Application software; Data analysis; Earth; IEEE Computer Society Press; Image analysis; Meteorology; Satellite broadcasting; Soil; Turing machines; Vegetation mapping;
fLanguage :
English
Journal_Title :
IEEE Expert
Publisher :
ieee
ISSN :
0885-9000
Type :
jour
DOI :
10.1109/64.295136
Filename :
295136
Link To Document :
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