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Rethinking Sigma’s Graphical Architecture: An Extension to Neural Networks

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9782)

Abstract

The status of Sigma’s grounding in graphical models is challenged by the ways in which their semantics has been violated while incorporating rule-based reasoning into them. This has led to a rethinking of what goes on in its graphical architecture, with results that include a straightforward extension to feedforward neural networks (although not yet with learning).

Keywords

Cognitive architecture Graphical models Neural network 

Notes

Acknowledgments

This effort has been sponsored by the U.S. Army. Statements and opinions expressed do not necessarily reflect the position or the policy of the United States Government, and no official endorsement should be inferred. We would also like to thank Himanshu Joshi for useful discussions on neural networks in Sigma.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Paul S. Rosenbloom
    • 1
    • 2
  • Abram Demski
    • 1
    • 2
  • Volkan Ustun
    • 1
  1. 1.Institute for Creative TechnologiesUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA

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