We present a new algorithm for probabilistic planning with no observability. Our algorithm, called Probabilistic-FF, extends the heuristic forward-search machinery of Conformant-F...
We describe HDL, an algorithm that learns HTN domain descriptions by examining plan traces produced by an expert problem-solver. Prior work on learning HTN methods requires that a...
Much has been made of the need for academic planning research to orient towards real-world applications. In this paper, we relate our experience in adapting domain-independent pla...
We present an architecture that provides a robust, scalable and flexible software framework for planning and scheduling systems through the use of standardized industrial-strength...
Many scheduling problems are posed as optimization problems where the goal is to find a feasible schedule that maximizes the utilization of some resource. In some domains it is al...
Andrew M. Sutton, Adele E. Howe, L. Darrell Whitle...