Adaptive Genetic Programs via Reinforcement Learning
Created by W.Langdon from
gp-bibliography.bib Revision:1.8194
- @InProceedings{downing:2001:gecco,
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title = "Adaptive Genetic Programs via Reinforcement Learning",
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author = "Keith L. Downing",
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pages = "19--26",
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year = "2001",
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publisher = "Morgan Kaufmann",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO-2001)",
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editor = "Lee Spector and Erik D. Goodman and Annie Wu and
W. B. Langdon and Hans-Michael Voigt and Mitsuo Gen and
Sandip Sen and Marco Dorigo and Shahram Pezeshk and
Max H. Garzon and Edmund Burke",
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address = "San Francisco, California, USA",
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publisher_address = "San Francisco, CA 94104, USA",
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month = "7-11 " # jul,
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keywords = "genetic algorithms, genetic programming, Reinforcement
Learning, Baldwin Effect, Lamarckianism, Hybrid
Adaptive Systems",
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ISBN = "1-55860-774-9",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2001/d01.pdf",
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size = "8 page",
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abstract = "Reinforced Genetic Programming (RGP) enhances standard
tree-based genetic programming (GP) [7] with
reinforcement learning (RL)[11]. Essentially, leaf
nodes of GP trees become monitored action-selection
points, while the internal nodes form a decision tree
for classifying the current state of the problem
solver. Reinforcements returned by the problem solver
govern both fitness evaluation and intra-generation
learning of the proper actions to take at the selection
points. In theory, the hybrid RGP system hints of
mutual benefits to RL and GP in controller-design
applications, by, respectively, providing proper
abstraction spaces for RL search, and accelerating
evolutionary progress via Baldwinian or Lamarckian
mechanisms. In practice, we demonstrate RGP's
improvements over standard GP search on maze-search
tasks",
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notes = "GECCO-2001 A joint meeting of the tenth International
Conference on Genetic Algorithms (ICGA-2001) and the
sixth Annual Genetic Programming Conference (GP-2001)
Part of \cite{spector:2001:GECCO}",
- }
Genetic Programming entries for
Keith L Downing
Citations