Building Agents with Memory: An Approach using Genetically Programmed Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{silva:1999:BAMAAGPN,

• author = "Arlindo Silva and Ana Neves and Ernesto Costa",
• title = "Building Agents with Memory: An Approach using Genetically Programmed Networks",
• booktitle = "Proceedings of the Congress on Evolutionary Computation",
• year = "1999",
• editor = "Peter J. Angeline and Zbyszek Michalewicz and Marc Schoenauer and Xin Yao and Ali Zalzala",
• volume = "3",
• pages = "1824--1840",
• address = "Mayflower Hotel, Washington D.C., USA",
• publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
• month = "6-9 " # jul,
• organisation = "Congress on Evolutionary Computation, IEEE / Neural Networks Council, Evolutionary Programming Society, Galesia, IEE",
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, route and network planning, agent evolution, connectionist structures, distributed programs, evolutionary strategies, genetically programmed networks, memory mechanism, neural networks, rule based systems, distributed programming, knowledge based systems, neural nets, software agents",
• ISBN = "0-7803-5536-9 (softbound)",
• ISBN = "0-7803-5537-7 (Microfiche)",
• URL = "http://citeseer.ist.psu.edu/rd/6296950%2C420864%2C1%2C0.25%2CDownload/http://citeseer.ist.psu.edu/cache/papers/cs/20671/http:zSzzSzwww.dei.uc.ptzSz%7EernestozSzEvoCozSzpaperszSzpaperszSz1999zSzcec99_3.pdf/silva99building.pdf",
• URL = "http://citeseer.ist.psu.edu/silva99building.html",
• DOI = "doi:10.1109/CEC.1999.785496",
• abstract = "To achieve a high degree of autonomy, an agent usually needs some kind of memory mechanism. We present a new approach to the evolution of agents with memory, based on the use of genetically programmed networks. These are connectionist structures where each node has an associated program, evolved using genetic programming. Genetically programmed networks can easily be evolved into agents with very different architectures. We present experimental results from evolving genetically programmed networks as neural networks, distributed programs and rule based systems capable of solving problems where the use of memory by the agent is essential. Comparisons are made between the performance of these solutions and the performance of solutions obtained by other evolutionary strategies used to evolve agents with memory",
• notes = "CEC-99 - A joint meeting of the IEEE, Evolutionary Programming Society, Galesia, and the IEE.

  Library of Congress Number = 99-61143",

}

Genetic Programming entries for Arlindo Ferreira da Silva Ana Paula Neves F Silva Ernesto Costa

Citations