Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
Powerful applications can be implemented using command scripts. A command script is a program written by one user, called a writer, and made available to another user, called the ...
This work considers the problem of minimizing the power consumption for real-time scheduling on processors with discrete operating modes. We provide a model for determining the ex...
Planning under uncertainty involves two distinct sources of uncertainty: uncertainty about the effects of actions and uncertainty about the current state of the world. The most wi...
Currently, the most effective complete SAT solvers are based on the DPLL algorithm augmented by clause learning. These solvers can handle many real-world problems from application...
Philipp Hertel, Fahiem Bacchus, Toniann Pitassi, A...