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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.
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on (Volume:6 )
Date of Conference: 15-19 June 2004