In this article we consider the issue of optimal control in collaborative multi-agent systems with stochastic dynamics. The agents have a joint task in which they have to reach a ...
Krylov-subspace based methods for generating low-order models of complicated interconnect are extremely effective, but there is no optimality theory for the resulting models. Alte...
— This paper proposes a high-level Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, whe...
— In this paper we study the relationship between the parameter θ, used in the design of the MinMax controller, and the conditioning of the approximate algebraic Riccati equatio...
Lizette Zietsman, Katie A. Evans, J. Teye Brown, R...
Abstract. Hierarchical (H)-matrices approximate full or sparse matrices using a hierarchical data sparse format. The corresponding H-matrix arithmetic reduces the time complexity o...