Evolvable Modeling: Structural Adaptation Through Hierarchical Evolution for 3-D Model-based Vision

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{FS93-04-021,

• author = "Thang C. Nguyen and David E. Goldberg and Thomas S. Huang",
• title = "Evolvable Modeling: Structural Adaptation Through Hierarchical Evolution for {3-D} Model-based Vision",
• booktitle = "Machine Learning in Computer Vision: What, Why, and How?",
• year = "1993",
• editor = "Kevin Bowyer and Lawrence Hall",
• series = "AAAI Fall Symposium Series",
• pages = "100--104",
• publisher = "AAAI",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-0-929280-53-0",
• URL = "http://www.aaai.org/Library/Symposia/Fall/1993/fs93-04-021.php",
• URL = "http://www.aaai.org/Papers/Symposia/Fall/1993/FS-93-04/FS93-04-021.pdf",
• size = "5 pages",
• abstract = "This paper presents a system that lets 3-D models evolve over time, eventually producing novel models that are more desirable than initial models. The algorithm starts with some crude models given by the user, or randomly-generated models from a given model-grammar with generic design rules and loose constraints. The underlying philosophy here is to gradually evolve the initial models into structurally novel and/or parametrically refined models over many generations. There is a close analogue in the evolution of species where better-fit species gradually emerge and form specialized niches, a highly efficient process of complex structural and functional optimization. Simulation results for model jet plane design illustrate that our approach to model design and refinement is both feasible and effective.",
• notes = "See also Technical report \cite{nguyen:emsat3d}",

}

Genetic Programming entries for Thang C Nguyen David E Goldberg Thomas S Huang

Citations