An approach to action planning based on simulated annealing

Author

Júnior, Ricardo Rames Basílio ; Lopes, Carlos Roberto

Author_Institution

Fac. de Comput., Univ. Fed. de Uberlandia (UFU), Uberlandia, Brazil

fYear

2012

fDate

14-17 Oct. 2012

Firstpage

2085

Lastpage

2090

Abstract

A number of new heuristic search methods have been developed in the field of automated planning over the last years. Enforced hill climbing (EHC) is a method that has been frequently used in several AI planning systems. This method presents a better performance compared to other methods in many planning domains, but it has some weaknesses. In this paper we investigate the use of a global search method based on simulated annealing. Preliminary results show significant results compared to algorithms based on enforced hill climbing.

Keywords

planning (artificial intelligence); search problems; simulated annealing; AI planning system; EHC method; action planning; artificial intelligence; enforced hill climbing method; global search method; heuristic search method; simulated annealing; Heuristic algorithms; Linear programming; Planning; Search problems; Simulated annealing; Space exploration; Temperature measurement; Enforced Hill Climbing; Fast Forward; Planning; Simulated Annealing;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on

Conference_Location

Seoul

Print_ISBN

978-1-4673-1713-9

Electronic_ISBN

978-1-4673-1712-2

Type

conf

DOI

10.1109/ICSMC.2012.6378047

Filename

6378047