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Factored planning using decomposition trees

Date

Authors

Kelareva, Elena

Buffet, Olivier

Huang, Jinbo

Thiebaux, Sylvie

Publisher

Carnegie Mellon University

Abstract

Improving AI planning algorithms relies on the ability to exploit the structure of the problem at hand. A promising direction is that of factored planning, where the domain is partitioned into subdomains with as little interaction as possible. Recent work

URI

http://hdl.handle.net/1885/29836

Collections

Open Access Research

Source

Proceedings of the International Joint Conference on Artificial Intelligence

Type

Conference paper

Restricted until

2037-12-31

Downloads

File

Description

01_Kelareva_Factored_planning_using_2007.pdf (25.91 KB)

02_Kelareva_Factored_planning_using_2007.pdf (43.92 KB)

03_Kelareva_Factored_planning_using_2007.pdf (233.08 KB)

04_Kelareva_Factored_planning_using_2007.pdf (299.98 KB)