Augmenting Collective Adaptation with Simple Process Agents

Created by W.Langdon from gp-bibliography.bib Revision:1.7970

@InProceedings{Haynes:1997:aaaiMAL,

• author = "Thomas Haynes",
• title = "Augmenting Collective Adaptation with Simple Process Agents",
• booktitle = "Papers from the AAAI Workshop on Multiagent Learning",
• year = "1997",
• editor = "Sandip Sen",
• pages = "41--46",
• organisation = "AAAI",
• note = "Published in AAAI Technical Report WS-97-03",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://www.aaai.org/Papers/Workshops/1997/WS-97-03/WS97-03-008.pdf",
• size = "6 pages",
• abstract = "We have integrated the distributed search of genetic programming based systems with collective memory to form a collective adaptation search method. Such a system significantly improves search as problem complexity is increased. However, there is still considerable scope for improvement. In collective adaptation, search agents gather knowledge of their environment and deposit it in a central information repository. Process agents are then able to manipulate that focused knowledge, exploiting the exploration of the search agents. We examine the utility of increasing the capabilities of the centralised process agents.",
• notes = "http://www.aaai.org/Library/Workshops/ws97-03.php",

}

Genetic Programming entries for Thomas D Haynes

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