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An Action Guided Constraint Satisfaction Technique for Planning Problem
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Author(s): Xiao Jiang (Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration, Ministry of Industry and Information Technology, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China), Pingyuan Cui (Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration, Ministry of Industry and Information Technology, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China), Rui Xu (Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration, Ministry of Industry and Information Technology, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China), Ai Gao (Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration, Ministry of Industry and Information Technology, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China)and Shengying Zhu (Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration, Ministry of Industry and Information Technology, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China)
Copyright: 2016
Volume: 8
Issue: 3
Pages: 15
Source title:
International Journal of Software Science and Computational Intelligence (IJSSCI)
Editor(s)-in-Chief: Brij Gupta (Asia University, Taichung City, Taiwan)and Andrew W.H. Ip (University of Saskatchewan, Canada)
DOI: 10.4018/IJSSCI.2016070103
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Abstract
This paper presents an action guided constraint satisfaction technique for planning problem. Different from the standard algorithms which are almost domain independence and cannot reflect the characteristics of the planning progress, this paper discusses how the action rules in planning act in constraint satisfaction problems. Based on the conclusion, an action directed constraint is proposed to guide the variable selected procedure in constraint satisfaction problems. Through theoretical analysis, this technique is prior an order of magnitude in variable select procedure over the ordinary heuristic technique and can be used in constraint-programmed planning problem generally. With the simulation experiments it shows that the algorithm with action guided constraint can effectively reduce the number of constraint checks during the planning procedure and has a better performance on total running time over the standard version.
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