Intelligence is a lot of things so no one single definition   
   is necessarily adequate. Still, as a WORKING definition   
   I accept Werbos': "a system to handle all of the calculations   
   from crude inputs through to overt actions in an adaptive   
   way so as to maximize some measure of performance over   
   time." (P. J. Werbos, IEEE Trans. Systems, Man, and   
   Cybernetics, 1987, pg 7) Steinbuch and Schmitt (Adaptive   
   systems using learning matrices, in Biocybernetics in   
   Avionics, Gordon and Breach, 1967, pp 751-768) may   
   have build the first intelligent machine according to this   
   definition.  Of course one can have an artificial intelligence   
   without claiming it is in any way as smart as a human.   
        Computational complexity appears to be the biggest   
   stumbling block standing in the way of efforts to build   
   more capable AIs. In my "Asa H" project I seek to control   
   complexity using some of the same methods that humans   
   use (R. Jones, Asa H: A hierarchical architecture for   
   software agents, Transactions of the Kansas Academy of   
   Science, vol. 109, No. 3/4, 2006, pp 159-167, available   
   through www.bioone.org or www.jstor.org), including:   
   1. category/concept formation/maintenance by clustering/   
       vector quantization   
   2. hierarchical organization/operation   
   3. running on parallel processors (or distributed across the   
       web   
   4. avoiding search when the previous match remains   
       adequate   
   5. simultaneous use of multiple specialized copies (society   
       of agents)   
   6. sequentially running multiple generations of copies/   
       agents   
   7. evaluation/learning on multiple time scales   
      
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