• DocumentCode
    2706034
  • Title

    On the complexity of computing equilibria for nonsymmetric analog networks

  • Author

    Miller, Douglas A. ; Sucker, S.W.

  • Author_Institution
    Comput. Vision & Robotics Lab., McGill Univ., Montreal, Que., Canada
  • fYear
    1991
  • fDate
    8-14 Jul 1991
  • Firstpage
    313
  • Abstract
    The authors ask what is the complexity of computing equilibria for physically realizable analog networks like those of J.J. Hopfield (1984) and T.J. Sejnowski (1981) with arbitrary connectivity. It is shown that, if the amplifiers are piecewise-linear, then such networks are instances of a game-theoretic model known as polymatrix games. Equilibria for the latter may be computed by vertex pivoting algorithms similar to the simplex method for linear programming, which are in practice of low order polynomial complexity. These algorithms appear to be the only ones both guaranteed to work and which are polynomial in practice. These results suggest that networks with few nonstable equilibria would be computationally attractive
  • Keywords
    computational complexity; game theory; linear programming; matrix algebra; neural nets; polynomials; Lemke´s algorithm; complementarity problems; computational complexity; equilibria; linear programming; neural nets; nonsymmetric analog networks; polymatrix games; polynomial complexity; Analog computers; Biology computing; Computer networks; Computer vision; Intelligent robots; NP-hard problem; Physics computing; Piecewise linear techniques; Polynomials; Robot vision systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-0164-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.155354
  • Filename
    155354