HANDLING UNCERTAINTY IN LEAST COMMITTED GRAPHPLAN: A CONFORMANT APPROACH
An artificial intelligent planner called Conformant Least Committed Graphplan(CLCGP) is proposed in this paper. This planner can handle uncertainty even without sensory information, which means it is possible to find valid plans no matter which of the allowed states the world is actually in.CLCGP is based on the famous planner LCGP, which has been prove to have great success in solving classic planning domains. The basic idea of this algorithm is to develop separate least committed planning graph for each possible world. The planner is implemented in common lisp and tested on a IBM RS6000 machine, empirical results show that CLCGP performs significantly better than the famous conformant planner CGP.
Intelligent planning conformant planning Graphplan Least-Commitment
JING-BO ZHANG YOU-HONG ZHANG WEN-XIANG GU JIA-NAN WANG
Department of Computer Science, Northeast Normal University, Changchun, Jilin, 130024, China College of Science, Foshan University, China, Foshan, 528000, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
107-112
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）