This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...
Online learning algorithms have impressive convergence properties when it comes to risk minimization and convex games on very large problems. However, they are inherently sequenti...
Daniel Hsu, Nikos Karampatziakis, John Langford, A...
Mathematical programs with nonlinear complementarity constraints are reformulated using better-posed but nonsmooth constraints. We introduce a class of functions, parameterized by...
Sequential selection, introduced for Evolution Strategies (ESs) with the aim of accelerating their convergence, consists in performing the evaluations of the different offspring...
Sequential selection was introduced for Evolution Strategies (ESs) with the aim of accelerating their convergence— performing the evaluations of the different offspring sequen...