Using genetic programming to learn and improve control knowledge
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @Article{aler:2002:AI,
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author = "Ricardo Aler and Daniel Borrajo and Pedro Isasi",
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title = "Using genetic programming to learn and improve control
knowledge",
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journal = "Artificial Intelligence",
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year = "2002",
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volume = "141",
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number = "1-2",
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pages = "29--56",
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month = oct,
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keywords = "genetic algorithms, genetic programming, Speedup
learning, Multi-strategy learning, Planning",
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URL = "http://scalab.uc3m.es/~dborrajo/papers/aij-evock.ps.gz",
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URL = "http://citeseer.ist.psu.edu/511810.html",
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DOI = "doi:10.1016/S0004-3702(02)00246-1",
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abstract = "The purpose of this article is to present a
multi-strategy approach to learn heuristics for
planning. This multi-strategy system, called
HAMLET-EVOCK, combines a learning algorithm specialised
in planning () and a genetic programming (GP) based
system (: Evolution of Control Knowledge). Both systems
are able to learn heuristics for planning on their own,
but both of them have weaknesses. Based on previous
experience and some experiments performed in this
article, it is hypothesised that handicaps are due to
its example-driven operators and not having a way to
evaluate the usefulness of its control knowledge. It is
also hypothesized that even if control knowledge is
sometimes incorrect, it might be easily correctable.
For this purpose, a GP-based stage is added, because of
its complementary biases: GP genetic operators are not
example-driven and it can use a fitness function to
evaluate control knowledge. and are combined by seeding
initial population with control knowledge. It is also
useful for to start from a knowledge-rich population
instead of a random one. By adding the GP stage to ,
the number of solved problems increases from 58% to 85%
in the blocks world and from 50% to 87% in the
logistics domain (0% to 38% and 0% to 42% for the
hardest instances of problems considered).",
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notes = "Hamlet, EvoCK, PRODIGY 4.0",
- }
Genetic Programming entries for
Ricardo Aler Mur
Daniel Borrajo
Pedro Isasi Vinuela
Citations