Several formalisms exist to express and solve decision problems. Each is designed to capture different kinds of knowledge: utilities expressing preferences, uncertainties on the en...
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
In this paper we investigate and compare multi-objective and weighted single objective approaches to a real world workforce scheduling problem. For this difficult problem we consid...
Peter I. Cowling, Nic Colledge, Keshav P. Dahal, S...
We propose a new randomized algorithm for maintaining a set of clusters among moving nodes in the plane. Given a specified cluster radius, our algorithm selects and maintains a va...
Jie Gao, Leonidas J. Guibas, John Hershberger, Li ...
Partially Observable Markov Decision Processes (POMDPs) provide an appropriately rich model for agents operating under partial knowledge of the environment. Since finding an opti...
Yan Virin, Guy Shani, Solomon Eyal Shimony, Ronen ...