DocumentCode :
2918312
Title :
Automated dynamic planning and execution for a partially observable game model: Tsunami City search and rescue
Author :
Vaccaro, James ; Guest, Clark
Author_Institution :
Lockheed Martin Corp., San Diego, CA
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
3685
Lastpage :
3694
Abstract :
This paper addresses the problem of autonomous dynamic planning and execution (ADP&E) for partially observable model environments. There are three accomplishments illustrated in this paper: (1) develop an ADP&E implementation framework for planning and executing in partially observable model environments, (2) design and implement a methodology for adapting planner parameters to improve the overall planning process, and (3) demonstrate the utility of the planning process on a large complex application (i.e., city search and rescue operations).
Keywords :
game theory; planning; automated dynamic planning; partially observable game model; rescue operations; Automata; Cities and towns; Decision trees; Process planning; Search methods; State feedback; State-space methods; Stochastic systems; Time measurement; Tsunami;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4631297
Filename :
4631297
Link To Document :
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