— Multi-robot systems require efficient and accurate planning in order to perform mission-critical tasks. However, algorithms that find the optimal solution are usually computa...
Abstract. We propose a randomized method for general convex optimization problems; namely, the minimization of a linear function over a convex body. The idea is to generate N rando...
Fabrizio Dabbene, P. S. Shcherbakov, Boris T. Poly...
In this paper; we describe optimal algorithmsfor incorporating error recovery in the imprecise computation model. In that model eack task compriser a mandatory and an optional par...
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
Pradeep Varakantham, Janusz Marecki, Yuichi Yabu, ...
Spectral methods for embedding graphs and immersing data manifolds in low-dimensional speaces are notoriously unstable due to insufficient and/or numberically ill-conditioned con...