X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=doc%2Fsource%2Foverview.rst;h=37e467a413172a447f6f69ab89e2239f33f58769;hb=4c946acce00821cab415ca7ed3af30df2ccf120d;hp=98353b279826b1887c1798a43dd8b51f4f190ffd;hpb=b934f519ba41db6fe6b4fb025b13ee9718f27be6;p=dunshire.git diff --git a/doc/source/overview.rst b/doc/source/overview.rst index 98353b2..37e467a 100644 --- a/doc/source/overview.rst +++ b/doc/source/overview.rst @@ -1,15 +1,15 @@ Overview -------- -Dunshire is a `CVXOPT `_-based library for solving -linear (cone) games. The notion of a symmetric linear (cone) game was -introduced by Gowda and Ravindran [GowdaRav]_, and extended by -Orlitzky to asymmetric cones with two interior points. +Dunshire is a library for solving linear games over symmetric +cones. The notion of a symmetric linear (cone) game was introduced by +Gowda and Ravindran [GowdaRav]_, and extended by Orlitzky to +asymmetric cones with two interior points. The state-of-the-art is that only symmetric games can be solved efficiently, and thus the linear games supported by Dunshire are a -bastard of the two: the cones are symmetric, but the players get to -choose two interior points. +compromise between the two: the cones are symmetric, but the players +get to choose two interior points. In this game, we have two players who are competing for a "payoff." There is a symmetric cone :math:`K`, a linear transformation :math:`L` @@ -34,10 +34,10 @@ and player two chooses a :math:`\bar{y}` from That ends the turn, and player one is paid :math:`\left\langle L\left(\bar{x}\right),\bar{y}\right\rangle` out of player two's -pocket. As is usual to assume in game theory, we suppose that player -one wants to maximize his worst-case payoff, and that player two wants -to minimize his worst-case *payout*. In other words, player one wants -to solve the optimization problem, +pocket. As is usual in game theory, we suppose that player one wants +to maximize his worst-case payoff, and that player two wants to +minimize his worst-case *payout*. In other words, player one wants to +solve the optimization problem, .. math:: \text{find }