Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
A helicopter agent has to plan trajectories to track multiple ground targets from the air. The agent has partial information of each target's pose, and must reason about its u...
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...
We develop a methodology for evaluating a decision strategy generated by a stochastic optimization model. The methodology is based on a pilot study in which we estimate the distri...
Robert Rush, John M. Mulvey, John E. Mitchell, Tho...
In this paper, a market-based decomposition method for decomposable linear systems is developed. The solution process iterates between a master problem that solves the market-matc...