Hierarchical Evolution of Neural Networks

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

@InProceedings{Moriarty:1998:henn,

• author = "David E. Moriarty and Risto Miikkulainen",
• title = "Hierarchical Evolution of Neural Networks",
• booktitle = "Proceedings of the 1998 IEEE World Congress on Computational Intelligence",
• year = "1998",
• pages = "428--433",
• address = "Anchorage, Alaska, USA",
• month = "5-9 " # may,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, SANE system, hierarchical approach, hierarchical evolution, network-level exploitive search, neural networks, neuro-evolution, neuron-level exploratory search, robot arm manipulation task, manipulator kinematics, neural nets",
• ISBN = "0-7803-4869-9",
• file = "c074.pdf",
• URL = "http://nn.cs.utexas.edu/downloads/papers/moriarty.icec98.ps.gz",
• DOI = "doi:10.1109/ICEC.1998.699793",
• size = "6 pages",
• abstract = "In most applications of neuro-evolution, each individual in the population represents a complete neural network. Retent work on the SANE system, however, has demonstrated that evolving individual neurons often produces a more efficient genetic search. This paper demonstrates that while SANE can solve easy tasks very quickly, it often stalls in larger problems. A hierarchical approach to neuro-evolution is presented that overcomes SANE' s difficul ties by integrating both a neuron-level exploratory search and a network-level exploitive search. In a robot arm manipulation task, the hierarchical approach outperforms both a neuron-based search and a network-based search.",
• notes = "ICEC-98 Held In Conjunction With WCCI-98 --- 1998 IEEE World Congress on Computational Intelligence",

}

Genetic Programming entries for David E Moriarty Risto Miikkulainen

Citations