Evolution of Mapmaking Ability: Strategies for the evolution of learning, planning, and memory using genetic programming
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- @InProceedings{andre:maps,
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author = "David Andre",
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title = "Evolution of Mapmaking Ability: Strategies for the
evolution of learning, planning, and memory using
genetic programming",
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booktitle = "Proceedings of the 1994 IEEE World Congress on
Computational Intelligence",
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year = "1994",
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volume = "1",
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pages = "250--255",
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address = "Orlando, Florida, USA",
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month = "27-29 " # jun,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming, evolved
representations, gold collection, information encoding,
intelligent agent, learning, mapmaking evolution;
memory, multi-phasic fitness environment, planning,
brain models, cartography, cognitive systems, learning
(artificial intelligence), planning (artificial
intelligence)",
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DOI = "doi:10.1109/ICEC.1994.350007",
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size = "6 pages",
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abstract = "An essential component of an intelligent agent is the
ability to observe, encode, and use information about
its environment. Traditional approaches to genetic
programming have focused on evolving functional or
reactive programs with only a minimal use of state.
This paper presents an approach for investigating the
evolution of learning, planning, and memory using
genetic programming. The approach uses a multi-phasic
fitness environment that enforces the use of memory and
allows fairly straightforward comprehension of the
evolved representations. An illustrative problem of
`gold' collection is used to demonstrate the usefulness
of the approach. The results indicate that the approach
can evolve programs that store simple representations
of their environments and use these representations to
produce simple plans",
- }
Genetic Programming entries for
David Andre
Citations