TY - GEN
T1 - An admissible HTN planning heuristic
AU - Bercher, Pascal
AU - Behnke, Gregor
AU - Höller, Daniel
AU - Biundo, Susanne
PY - 2017
Y1 - 2017
N2 - Hierarchical task network (HTN) planning is wellknown for being an efficient planning approach. This is mainly due to the success of the HTN planning system SHOP2. However, its performance depends on hand-designed search control knowledge. At the time being, there are only very few domainindependent heuristics, which are designed for differing hierarchical planning formalisms. Here, we propose an admissible heuristic for standard HTN planning, which allows to find optimal solutions heuristically. It bases upon the so-called task decomposition graph (TDG), a data structure reflecting reachable parts of the task hierarchy. We show (both in theory and empirically) that rebuilding it during planning can improve heuristic accuracy thereby decreasing the explored search space. The evaluation further studies the heuristic both in terms of plan quality and coverage.
AB - Hierarchical task network (HTN) planning is wellknown for being an efficient planning approach. This is mainly due to the success of the HTN planning system SHOP2. However, its performance depends on hand-designed search control knowledge. At the time being, there are only very few domainindependent heuristics, which are designed for differing hierarchical planning formalisms. Here, we propose an admissible heuristic for standard HTN planning, which allows to find optimal solutions heuristically. It bases upon the so-called task decomposition graph (TDG), a data structure reflecting reachable parts of the task hierarchy. We show (both in theory and empirically) that rebuilding it during planning can improve heuristic accuracy thereby decreasing the explored search space. The evaluation further studies the heuristic both in terms of plan quality and coverage.
UR - http://www.scopus.com/inward/record.url?scp=85031932647&partnerID=8YFLogxK
U2 - 10.24963/ijcai.2017/68
DO - 10.24963/ijcai.2017/68
M3 - Conference contribution
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 480
EP - 488
BT - 26th International Joint Conference on Artificial Intelligence, IJCAI 2017
A2 - Sierra, Carles
PB - International Joint Conferences on Artificial Intelligence
T2 - 26th International Joint Conference on Artificial Intelligence, IJCAI 2017
Y2 - 19 August 2017 through 25 August 2017
ER -