Heuristics for Cost-Optimal Classical Planning Based on Linear Programming
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Best Papers from Sister Conferences Track. Pages 4303-4308.
Abstract
Many heuristics for cost-optimal planning are based on linear programming. We cover several interesting heuristics of this type by a common framework that fixes the objective function of the linear program. Within the framework, constraints from different heuristics can be combined in one heuristic estimate which dominates the maximum of the component heuristics. Different heuristics of the framework can be compared on the basis of their constraints. We present theoretical results on the relation between existing heuristics and experimental results that demonstrate the potential of the proposed framework.
@inproceedings{ijcai2015p612,
title = {Heuristics for Cost-Optimal Classical Planning Based on Linear Programming},
author = {Pommerening, Florian and Röger, Gabriele and Helmert, Malte and Bonet, Blai},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {4303--4308},
year = {2015},
month = {7},
note = {Best Papers from Sister Conferences Track},
url = {https://ijcai.org/proceedings/2015/612},
}
TY - CPAPER TI - Heuristics for Cost-Optimal Classical Planning Based on Linear Programming AU - Pommerening, Florian AU - Röger, Gabriele AU - Helmert, Malte AU - Bonet, Blai T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 4303 EP - 4308 UR - https://ijcai.org/proceedings/2015/612 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: