Decision-theoretic military operations planning
Aberdeen, Douglas; Thiebaux, Sylvie; Zhang, Lin
Description
Military operations planning involves concurrent actions, resource assignment, and conflicting costs. Individual tasks sometimes fail with a known probability, promoting a decision-theoretic approach. The planner must choose between multiple tasks that achieve similar outcomes but have different costs. The military domain is particularly suited to automated methods because hundreds of tasks, specified by many planning staff, need to be quickly and robustly coordinated. The authors are not aware...[Show more]
dc.contributor.author | Aberdeen, Douglas | |
---|---|---|
dc.contributor.author | Thiebaux, Sylvie | |
dc.contributor.author | Zhang, Lin | |
dc.coverage.spatial | Whistler Canada | |
dc.date.accessioned | 2015-12-13T23:10:18Z | |
dc.date.available | 2015-12-13T23:10:18Z | |
dc.date.created | June 3 2004 | |
dc.identifier.isbn | 1577352009 | |
dc.identifier.uri | http://hdl.handle.net/1885/87394 | |
dc.description.abstract | Military operations planning involves concurrent actions, resource assignment, and conflicting costs. Individual tasks sometimes fail with a known probability, promoting a decision-theoretic approach. The planner must choose between multiple tasks that achieve similar outcomes but have different costs. The military domain is particularly suited to automated methods because hundreds of tasks, specified by many planning staff, need to be quickly and robustly coordinated. The authors are not aware of any previous planners that handle all characteristics of the operations planning domain in a single package. This paper shows that problems with such features can be successfully approached by real-time heuristic search algorithms, operating on a formulation of the problem as a Markov decision process. Novel automatically generated heuristics, and classic caching methods, allow problems of interesting sizes to be handled. Results are presented on data provided by the Australian Defence Science and Technology Organisation. | |
dc.publisher | AAAI Press | |
dc.relation.ispartofseries | International Conference on Automated Planning and Scheduling (ICAPS 2004) | |
dc.source | ICAPS 2004: Proceedings of the Fourteenth International Conference on Automated Planning and Scheduling | |
dc.source.uri | http://www.cc.gatech.edu/fac/Sven.Koenig/icaps/conferences.html | |
dc.source.uri | http://users.rsise.anu.edu.au/~thiebaux/papers/icaps04.pdf | |
dc.subject | Keywords: Caching methods; Military operations planning; Task effects; Algorithms; Costs; Dynamic programming; Markov processes; Military operations; Planning; Decision theory | |
dc.title | Decision-theoretic military operations planning | |
dc.type | Conference paper | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
dc.date.issued | 2004 | |
local.identifier.absfor | 080199 - Artificial Intelligence and Image Processing not elsewhere classified | |
local.identifier.ariespublication | MigratedxPub16656 | |
local.type.status | Published Version | |
local.contributor.affiliation | Aberdeen, Douglas, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Thiebaux, Sylvie, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Zhang, Lin, Commonwealth Department of Defence | |
local.bibliographicCitation.startpage | 402 | |
local.bibliographicCitation.lastpage | 412 | |
dc.date.updated | 2015-12-12T08:23:26Z | |
local.identifier.scopusID | 2-s2.0-13444288352 | |
Collections | ANU Research Publications |
Download
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.
Updated: 17 November 2022/ Responsible Officer: University Librarian/ Page Contact: Library Systems & Web Coordinator