A projection algorithm for strictly monotone linear complementarity problems
journal contributionposted on 2013-12-01, 00:00 authored by Erik Zawadski, Geoffrey J. Gordon, Andre Platzer
Complementary problems play a central role in equilibrium finding, physical simulation, and optimization. As a consequence, we are interested in understanding how to solve these problems quickly, and this often involves approximation. In this paper we present a method for approximately solving strictly monotone linear complementarity problems with a Galerkin approximation. We also give bounds for the approximate error, and prove novel bounds on perturbation error. These perturbation bounds suggest that a Galerkin approximation may be much less sensitive to noise than the original LCP.