Oscar: A cognitive architecture for intelligent agents

Abstract The “grand problem” of AI has always been to build artificial agents of human-level intelligence, capable of operating in environments of real-world complexity. OSCAR is a cognitive architecture for such agents, implemented in LISP. OSCAR is based on my extensive work in philosophy concerning both epistemology and rational decision making. This paper provides a detailed overview of OSCAR. The main conclusions are that such agents must be capablew of operating against a background of pervasive ignorance, because the real world is too complex for them to know more than a small fraction of what is true. This is handled by giving the agent the power to reason defeasibily. The OSCAR system of defeasible reasoning is sketched. It is argued that if epistemic cognition must be defeasible, planning must also be done defeasibly, and the best way to do that is to reason defeasibly about plans. A sketch is given about how this might work.
Keywords No keywords specified (fix it)
Categories
Options
 Save to my reading list
Follow the author(s)
My bibliography
Export citation
Find it on Scholar
Edit this record
Mark as duplicate
Revision history Request removal from index
 
Download options
PhilPapers Archive


Upload a copy of this paper     Check publisher's policy on self-archival     Papers currently archived: 5,672
External links
  •   Try with proxy.
  •   Try with proxy.
  •   Try with proxy.
  • Through your library Only published papers are available at libraries

    Similar books and articles

    Analytics

    Monthly downloads

    Added to index

    2009-01-28

    Total downloads

    26 ( #47,624 of 549,047 )

    Recent downloads (6 months)

    4 ( #19,186 of 549,047 )

    How can I increase my downloads?


    My notes
    Sign in to use this feature


    Discussion
    Start a new thread
    Order:
    There  are no threads in this forum
    Nothing in this forum yet.

    Other forums