We develop a decision-theoretic method that yields approximate, low cost troubleshooting plans by making more relevant observations and devoting more time to generate a plan. The ...
Autonomous systems operating in real-world environments must be able to plan, schedule, and execute missions while robustly adapting to uncertainty and disturbances. Previous work...
Julie A. Shah, John Stedl, Brian C. Williams, Paul...
The New Millennium Remote Agent (NMRA) will be the rst on-board AI system to control an actual spacecraft. The spacecraft domain raises a number of challenges for planning and exe...
Barney Pell, Erann Gat, Ron Keesing, Nicola Muscet...
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 ...
We propose a framework for policy generation in continuoustime stochastic domains with concurrent actions and events of uncertain duration. We make no assumptions regarding the co...