Abstract. In this work we present an assessment of state-of-the-art Boolean optimization solvers from different AI communities on over-subscription planning problems. The goal of t...
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
– In this paper, we evaluate the performance of two candidate formulations for distributed motion planning of robot collectives within an Artificial Potential Field (APF) framewo...
Accessing data from numerous widely-distributed sources poses signi cant new challenges for query optimization and execution. Congestion and failures in the network can introduce ...
Laurent Amsaleg, Michael J. Franklin, Anthony Toma...
As no plan can cover all possible contingencies, the ability to detect failures during plan execution is crucial to the robustness of any autonomous system operating in a dynamic ...