IDEAS home Printed from
   My bibliography  Save this paper

Analogy-Making as a Complex Adaptive System


  • Melanie Mitchell


This paper describes a computer program, called Copycat, that models how people make analogies. It might seem odd to include such a topic in a collection of papers mostly on the immune system. However, the immune system is one of many systems in nature in which a very large collection of relatively simple agents, operating with no central control and limited communication among themselves, collectively produce highly complex, coordinated, and adaptive behavior. Other such systems include the brain, colonies of social insects, economies, and ecologies. The general study of how such emergent adaptive behavior comes about has been called the study of "complex adaptive systems". The Copycat program is meant to model human cognition, and its major contribution is to show how a central aspect of cognition can be modeled as the kind of decentralized, distributed complex system described above. In doing so it proposes principles that I believe are common to all complex adaptive systems, and that are particularly relevant to the study of immunology. Copycat was developed by Douglas Hofstadter and myself, and has been described previously in [3, 10, 11, 16, 17]. This paper summarizes these earlier works, and makes explicit links to the immune system.

Suggested Citation

  • Melanie Mitchell, 2000. "Analogy-Making as a Complex Adaptive System," Working Papers 00-04-024, Santa Fe Institute.
  • Handle: RePEc:wop:safiwp:00-04-024

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item


    Analogy; perception; cognition; immune system.;

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wop:safiwp:00-04-024. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.