Symbolic Merge-and-Shrink for Cost-Optimal Planning
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 2394-2399.
Abstract
Symbolic PDBs and Merge-and-Shrink (M&S) are two approaches to derive admissible heuristics for optimal planning. We present a combination of these techniques, Symbolic Merge-and-Shrink (SM&S), which uses M&S abstractions as a relaxation criterion for a symbolic backward search. Empirical evaluation shows that SM&S has the strengths of both techniques deriving heuristics at least as good as the best of them for most domains.
Álvaro Torralba Arias de Reyna, Carlos Linares López, and Daniel Borrajo. 2013. Symbolic Merge-and-Shrink for Cost-Optimal Planning. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13. IJCAI, 2394–2399. https://ijcai.org/proceedings/2013/352
de Reyna, Á. T. A., Linares López, C., & Borrajo, D. (2013). Symbolic Merge-and-Shrink for Cost-Optimal Planning. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 (pp. 2394–2399). IJCAI. https://ijcai.org/proceedings/2013/352
@inproceedings{ijcai2013p352,
title = {Symbolic Merge-and-Shrink for Cost-Optimal Planning},
author = {de Reyna, Álvaro Torralba Arias and Linares López, Carlos and Borrajo, Daniel},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {2394--2399},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/352},
}
TY - CPAPER TI - Symbolic Merge-and-Shrink for Cost-Optimal Planning AU - de Reyna, Álvaro Torralba Arias AU - Linares López, Carlos AU - Borrajo, Daniel T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 2394 EP - 2399 UR - https://ijcai.org/proceedings/2013/352 ER -Copied
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