Title :
Iterative strengthening: an algorithm for generating anytime optimal plans
Author :
Calistri-Yeh, Randall J.
Author_Institution :
ORA, Ithaca, NY, USA
Abstract :
In order to perform adequately in real-world situations, a planning system must be able to find the “best” solution while still supporting anytime behavior. We have developed a method for incrementally optimizing plans called iterative strengthening that can be used in many situations where other optimization methods are not appropriate. In particular, iterative strengthening supports optimized planning within an “anytime” environment using multiple simultaneous optimizing parameters, and it can be adapted to support inadmissible heuristics and undecidable domains
Keywords :
iterative methods; optimisation; planning (artificial intelligence); anytime behavior; anytime optimal plans; inadmissible heuristics; iterative strengthening; multiple simultaneous optimizing parameters; optimization methods; optimized planning; planning system; real-world situations; Air transportation; Contracts; Engines; Government; Iterative algorithms; Iterative methods; Optimization methods; Switches; System testing; Time factors;
Conference_Titel :
Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-8186-6785-0
DOI :
10.1109/TAI.1994.346415
