Dilemmas in computational societies

by

Glance, N., S. and Hogg, T.

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Info: Proceedings of the First International Conference on Multi--Agent Systems (Conference proceedings), 1995, p. 117-124
Abstract:
World-wide interlinked computer networks are forming the foundation for computational societies of software agents. [SA] Already, these new societies have encountered problems endemic to human communities, such as overusing common resources with thrashing over virtual memory and competition by packets for network time. Unlike with human societies, these inefficiencies can be overcome by re-working the algorithms governing the protocols. However, the public good problem, in which a common good is available to all regardless of contribution, can arise computationally in more subtle ways. We discuss how this can happen using Braess' Paradox and demonstrate that adding resources to a computational system can counterintuitively lower the overall performance. This is thus a case in which distributed algorithms are provably unable to achieve globally optimal performance. We illustrate our claim using a genetic algorithm [GA] and computational ecosystem.
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BibTex:
@InProceedings{Glance:1995:DCS,
  title =        "Dilemmas in computational societies",
  author =       "Natalie S. Glance and Tad Hogg",
  pages =        "117--124",
  booktitle =    "Proceedings of the First International Conference on
                 Multi--Agent Systems",
  year =         "1995",
  publisher =    "MIT Press",
  address =      "San Francisco, CA",
  editor =       "Victor Lesser",
  abstract =     "World-wide interlinked computer networks are forming
                 the foundation for computational societies of software
                 agents. Already, these new societies have encountered
                 problems endemic to human communities, such as
                 overusing common resources with thrashing over virtual
                 memory and competition by packets for network time.
                 Unlike with human societies, these inefficiencies can
                 be overcome by re-working the algorithms governing the
                 protocols. However, the public good problem, in which a
                 common good is available to all regardless of
                 contribution, can arise computationally in more subtle
                 ways. We discuss how this can happen using Braess'
                 Paradox and demonstrate that adding resources to a
                 computational system can counterintuitively lower the
                 overall performance. This is thus a case in which
                 distributed algorithms are provably unable to achieve
                 globally optimal performance. We illustrate our claim
                 using a genetic algorithm and computational
                 ecosystem.",
}