Autonomous robots need to track objects. Object tracking relies on predefined robot motion and sensory models. Tracking is particularly challenging if the robots can actuate on th...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Autonomous robots use sensors to perceive and track objects in the world. Tracking algorithms use object motion models to estimate the position of a moving object. Tracking effic...
We consider a market model with one riskfree and one risky asset, in which the dynamics of the risky asset is governed by a geometric Brownian motion. In this market we consider a...
Abstract. We develop a partial equilibrium model to investigate the problem of optimal liquidation over a finite or infinite time horizon for an investor with large holdings in a r...