We propose a Gaussian process (GP) framework for robust inference in which a GP prior on the mixing weights of a two-component noise model augments the standard process over laten...
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
Random geometric graphs have been one of the fundamental models for reasoning about wireless networks: one places n points at random in a region of the plane (typically a square o...
Alan M. Frieze, Jon M. Kleinberg, R. Ravi, Warren ...
A wide variety of techniques for visual navigation using robot-mounted cameras have been described over the past several decades, yet adoption of optical flow navigation technique...
Jason Campbell, Rahul Sukthankar, Illah R. Nourbak...
We present a new algorithm for conformant probabilistic planning, which for a given horizon produces a plan that maximizes the probability of success under quantified uncertainty ...