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Immune evolutionary path planning with instance-learning for mobile robot under changing environment

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2 Author(s)
Meiyi Li ; Coll. of Inf. Sci. & Eng., Central South Univ., Changsha, China ; Zixing Cai

This paper has present an immune evolutionary planning and negating algorithm with instance-learning for mobile robot under changing environment, which combines immune principle in life science with instance-learning into evolutionary algorithm. Experiences (excellent individuals) in elapsed evolutionary process are stored by instances, and by means of instance-learning immune evolutionary algorithms can quickly plan global-optimal path. Then roles of instance-learning and immune are analyzed from mathematical analyses as well as simulating experiments.

Published in:

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on  (Volume:6 )

Date of Conference:

15-19 June 2004