An approach to Action Planning Based on Simulated Annealing

被引：0

作者：

Basilio Junior, Ricardo Rames ^{[1
]}

Lopes, Carlos Roberto ^{[1
]}

机构：

[1] Univ Fed Uberlandia, PPGCC Fac Comp, BR-38400 Uberlandia, MG, Brazil

来源：

PROCEEDINGS 2012 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2012年

关键词：

Fast Forward; Simulated Annealing; Enforced Hill Climbing; Planning; FF; SYSTEM;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：2085 / 2090

页数：6

共 16 条

[1] Fast forward planning by guided enforced hill climbing [J].

Akramifar, S. A. ;

Ghassem-Sani, G. .

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2010, 23 (08) :1327-1339

[2] Simulated annealing with restarts for the optimization of electromagnetic devices [J].

Alfonzetti, S ;

Dilettoso, E ;

Salerno, N .

IEEE TRANSACTIONS ON MAGNETICS, 2006, 42 (04) :1115-1118

[3] Macro-FF:: Improving AI planning with automatically learned macro-operators [J].

Botea, A ;

Enzenberger, M ;

Müller, M ;

Schaeffer, J .

JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2005, 24 :581-621

[4]

Bryce D., 2006, ICAPS 2006 5 INT PLA

[5] THERMODYNAMICAL APPROACH TO THE TRAVELING SALESMAN PROBLEM - AN EFFICIENT SIMULATION ALGORITHM [J].

CERNY, V .

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 1985, 45 (01) :41-51

[6]

Coles A., 2008, C AI ED 23 AAAI C AR

[7]

Coles A., 2007, J ARTIFICIAL INTELLI, P28

[8] STRIPS - NEW APPROACH TO APPLICATION OF THEOREM PROVING TO PROBLEM SOLVING [J].

FIKES, RE ;

NILSSON, NJ .

ARTIFICIAL INTELLIGENCE, 1971, 2 (3-4) :189-208

[9] Conformant planning via heuristic forward search: A new approach [J].

Hoffmann, J ;

Brafman, RI .

ARTIFICIAL INTELLIGENCE, 2006, 170 (6-7) :507-541

[10] The FF planning system: Fast plan generation through heuristic search [J].

Hoffmann, J ;

Nebel, B .

JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2001, 14 :253-302

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