Autonomous Robot Failure Recognition Design using Multi-Objective Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Zhang:2006:MLC,

• author = "Yang Zhang",
• title = "Autonomous Robot Failure Recognition Design using Multi-Objective Genetic Programming",
• booktitle = "2006 International Conference on Machine Learning and Cybernetics",
• year = "2006",
• pages = "4563--4568",
• month = aug,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "1-4244-0061-9",
• DOI = "doi:10.1109/ICMLC.2006.258378",
• abstract = "An evolutionary autonomous failure recognition approach is presented using multi-objective genetic programming in this paper. It is compared with the conventional robot failure classification algorithm. Detailed analysis of the evolved feature extractors is tempted on investigated problems. We conclude MOGP is an effective and practical way to automate the process of failure recognition system design with better recognition accuracy and more flexibility via optimising feature extraction stage.",
• notes = "Electronic and Electrical Engineering Department, The University of Sheffield, S1 3JD, UK",

}

Genetic Programming entries for Yang Zhang

Citations