In this project, we investigate the application of Gaussian process models for decision-making under uncertainty. Specifically, we consider a navigation problem where the energy costs are stochastic with unknown distributions and our goal is to find the most energy-efficient route. The project will develop models that can efficiently explore the road network with minimal prior data.