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Intelligent control with hierarchical stacked neural networks

  • US 7,152,051 B1
  • Filed: 09/30/2002
  • Issued: 12/19/2006
  • Est. Priority Date: 09/30/2002
  • Status: Active Grant
First Claim
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1. A stacked neural network, consisting essentially of:

  • a plurality of architecturally distinct, separately trainable, ordered neural networks of varying complexity;

    said plurality being organized in a linear hierarchy of complexity from lower to higher order/stages in a model of cognitive development, wherein output from each member at a respectively lower order/stage provides the input for the next respectively higher order/stage member, substantially without skipping order/stages;

    each member of said plurality feeding signals forward and back to other members of said plurality;

    said signals being defined in terms of actions available to said each member, said each member transforming actions from at least one member at a lower order/stage, to produce nonarbitrary organizations of said actions from said at least one member at a lower order/stage effective for completing new tasks of increased complexity;

    said nonarbitrary organizations being fed to at least one member at a higher order/stage; and

    said nonarbitrary organizations being modifiable by feedback signals from members at said higher order/stages.

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