EfficientIDC: a faster incremental dynamic controllability algorithm

摘要: The exact duration of an action generally cannot be predicted in advance. Temporal planning therefore tends to use upper bounds on durations, with the explicit or implicit assumption that if happens executed more quickly, plan will still succeed. However, this is often false: If we finish cooking too early, dinner cold before everyone at home and can eat. Simple Problems Uncertainty (STPUs) allow us model such situations. An STPU-based planner must then verify networks it generates are executable, captured by property dynamic controllability. FastIDC algorithm do incrementally during planning. In paper show method result traversing part a temporal network multiple times, constraints slowly tightening towards their final values. We present new uses additional analysis together different traversal strategy avoid behavior. has guaranteed time complexity lower than proven sound complete.