| Runtime Decision Sampling and Branch Utility Re-Evaluation in the Robust Execution of Contingent Plans (2008) | |||||||||||||||||
Abstract | |||||||||||||||||
| Abstract — Current planning algorithms have difficulty handling the complexity that is due to an increase in domain uncertainty, and especially in the case of multi-dimensional continuous spaces. Therefore, they produce plans that do not take into account numerous situations, such as faults or other changes in the planning domain itself and that can occur at runtime. Here, we present our approach to the robust execution of contingent plans, i.e. that involve conditional branches based on decision functions of the system state. We use a version of the Monte-Carlo simulation for Markov Decision Processes to re-evaluate branch utility values and branch conditions whenever an unpredictable event occur, based on health monitoring information at runtime. | |||||||||||||||||
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