We seek to increase user confidence in simulations as they are adapted to meet new requirements. Our approach includes formal representation of uncertainty, lightweight validation,...
Paul F. Reynolds Jr., Michael Spiegel, Xinyu Liu, ...
We present a discrete simulation model for software projects which explicitly takes a scheduling strategy as input. The model represents varying staff skill levels, component coup...
In order to interact successfully in social situations, a robot must be able to observe others' actions and base its own behavior on its beliefs about their intentions. Many ...
Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, ...
Abstract. We introduce a uniform framework for reasoning about infinitestate systems with unbounded control structures and unbounded data domains. Our framework is based on constr...
Ahmed Bouajjani, Peter Habermehl, Yan Jurski, Miha...