To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
The basic motivation behind this work is to tie together various computational complexity classes, whether over different domains such as the naturals or the reals, or whether de...
Abstract— Wireless ad hoc networks provide a useful communications infrastructure for the mobile battlefield. In this paper we apply and develop passive radio frequency signal s...
Jon Arnold, Nigel Bean, Miro Kraetzl, Matthew Roug...
We propose an analytic moment-based filter for nonlinear stochastic dynamic systems modeled by Gaussian processes. Exact expressions for the expected value and the covariance matr...
Marc Peter Deisenroth, Marco F. Huber, Uwe D. Hane...
Abstract. We present hardness results, approximation heuristics, and exact algorithms for bottleneck labeled optimization problems arising in the context of graph theory. This long...