Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
- In this article, we present an algorithm which is capable of transforming a gridded dogleg channel routing problem into a constraint programming (CP) problem. The transformed CP ...
I-Lun Tseng, Huan-Wen Chen, Che-I Lee, Adam Postul...
Abstract. This paper investigates the problem of autonomously allocating a large number of independent, equal sized tasks on a distributed heterogeneous grid-like platform, using o...
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
— Multi-robot systems require efficient and accurate planning in order to perform mission-critical tasks. However, algorithms that find the optimal solution are usually computa...