Linköping University, Sweden
Temporal Networks, Dynamic Controllability.
Informatics in Control, Automation and Robotics
Intelligent Control Systems and Optimization
Planning and Scheduling
Simulation and Modeling
Uncertainty in AI
Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where
some durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essential
to verify that such networks are dynamically controllable (DC) – executable regardless of the outcomes
of uncontrollable durations – and to convert them to an executable form. We use insights from incremental
DC verification algorithms to re-analyze the original verification algorithm. This algorithm, thought to be
pseudo-polynomial and subsumed by an O(n5) algorithm and later an O(n4) algorithm, is in fact O(n4) given
a small modification. This makes the algorithm attractive once again, given its basis in a less complex and
more intuitive theory. Finally, we discuss a change reducing the amount of work performed by the algorithm.