162,582 research outputs found

    A Numerical Algorithm to find Soft-Constrained Nash Equilibria in Scalar LQ-Games

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    In this paper we provide a numerical algorithm to calculate all soft-constrained Nash equilibria in a regular scalar indefinite linear-quadratic game.The algorithm is based on the calculation of the eigenstructure of a certain matrix.The analysis follows the lines of the approach taken by Engwerda in [7] to calculate the solutions of a set of scalar coupled feedback Nash algebraic Riccati equations.C63;C72;C73

    A Numerical Algorithm to find Soft-Constrained Nash Equilibria in Scalar LQ-Games

    No full text
    In this paper we provide a numerical algorithm to calculate all soft-constrained Nash equilibria in a regular scalar indefinite linear-quadratic game.The algorithm is based on the calculation of the eigenstructure of a certain matrix.The analysis follows the lines of the approach taken by Engwerda in [7] to calculate the solutions of a set of scalar coupled feedback Nash algebraic Riccati equations

    Linear Quadratic Games: An Overview

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    In this paper we review some basic results on linear quadratic differential games.We consider both the cooperative and non-cooperative case.For the non-cooperative game we consider the open-loop and (linear) feedback information structure.Furthermore the effect of adding uncertainty is considered.The overview is based on [9].Readers interested in detailed proofs and additional results are referred to this book.linear-quadratic games;Nash equilibrium;affine systems;solvability conditions;Riccati equations

    [Report to Chief J. E. Curry, by an unknown author #1]

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    Report to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney

    [Report to Chief J. E. Curry, by an unknown author #2]

    No full text
    Report to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney

    Calculation of an approximate solution of the infinite time-varying LQ-problem

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    Linear Programming;Algorithm;Optimal Control;operations research

    On the Sensitivity Matrix of the Nash Bargaining Solution

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    In this note we derive the sensitivity matrix of the Nash bargaining solution w.r.t. the disagreement point d.This first order derivative is completely specified in terms of the Pareto frontier function.We show that whenever one player increases his threatpoint always at least one player will loose utility: i.e. the dual result of Pareto optimality.Furthermore,the dmonotonicity property is easily re-established from this matrix.This matrix also enables us to consider the concept of local strong d-monotonicity.That is,under which conditions on the Pareto frontier function . an infinitesimal increase of di,while for each j = i, dj remains constant,it happens that agent i is the only one who s payoff increases.We show that for the Nash bargaining solution this question is closely related to non-negativity of the Hamiltonian matrix of . at the solution.Nash bargaining solution;d-monotonicity;diagonally dominant Stieltjes matrix
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