In autonomous robotics, so-called artificial potential fields are often used to plan and control the motion of a physical robot. In this paper, we propose to use an artificial e...
With the explosive growth of demand for services on the Internet, the networking infrastructure (routers, protocols, servers) is under considerable stress. Mechanisms are needed f...
In this paper, we study a sequential decision making problem. The objective is to maximize the average reward accumulated over time subject to temporal cost constraints. The novel...
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
In this paper, we set up a framework to study approximation of manipulation, control, and bribery in elections. We show existence of approximation algorithms (even fully polynomia...
Eric Brelsford, Piotr Faliszewski, Edith Hemaspaan...