In the field of robust optimization, the goal is to provide solutions to combinatorial problems that hedge against variations of the numerical parameters. This constitutes an effor...
Monaldo Mastrolilli, Nikolaus Mutsanas, Ola Svenss...
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Most algorithms for solving Markov decision processes rely on a discount factor, which ensures their convergence. It is generally assumed that using an artificially low discount f...
We consider the problem of computing -approximate Nash equilibria in network congestion games. The general problem is known to be PLS-complete for every > 0, but the reductions...
Simulation composability is a difficult capability to achieve due to the challenges of creating components, selecting combinations of components, and integrating the selected comp...
Michael Roy Fox, David C. Brogan, Paul F. Reynolds...