Hierarchical Evolution of Neural Networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Moriarty:1998:henn,
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author = "David E. Moriarty and Risto Miikkulainen",
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title = "Hierarchical Evolution of Neural Networks",
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booktitle = "Proceedings of the 1998 IEEE World Congress on
Computational Intelligence",
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year = "1998",
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pages = "428--433",
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address = "Anchorage, Alaska, USA",
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month = "5-9 " # may,
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publisher = "IEEE Press",
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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",
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ISBN = "0-7803-4869-9",
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file = "c074.pdf",
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URL = "http://nn.cs.utexas.edu/downloads/papers/moriarty.icec98.ps.gz",
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DOI = "doi:10.1109/ICEC.1998.699793",
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size = "6 pages",
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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.",
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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