In the model-based policy search approach to reinforcement learning (RL), policies are found using a model (or "simulator") of the Markov decision process. However, for ...
Abstract — In order to perform valid experiments, traffic generators used in network simulators and testbeds require up to date models of traffic as it exists on real network lin...
Abstract. Two main challenges of robot action planning in real domains are uncertain action effects and dynamic environments. In this paper, an instance-based action model is lear...
CIP is a model-based software development method for embedded systems. The problem of constructing an embedded system is decomposed into a functional and a connection problem. The ...
In this paper, we address the problem of discovering the 3D shape of a book surface from the shading information in a scanned document image. This shapefrom-shading problem is cha...