Planning with Continuous Resources in Stochastic Domains
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1244-1250.
Abstract
We consider the problem of optimal planning in stochastic domains with resource constraints, where resources are continuous and the choice of action at each step may depend on the current resource level. Our principal contribution is the HAO* algorithm, a generalization of the AO* algorithm that performs search in a hybrid state space that is modeled using both discrete and continuous state variables. The search algorithm leverages knowledge of the starting state to focus computational effort on the relevant parts of the state space. We claim that this approach is especially effective when resource limitations contribute to reachability constraints. Experimental results show its effectiveness in the domain that motivates our research – automated planning for planetary exploration rovers.
@inproceedings{ijcai2005p194,
title = {Planning with Continuous Resources in Stochastic Domains},
author = {Mausam and Benazera, Emmanuel and Brafman, Ronen I. and Meuleau, Nicolas and Hansen, Eric A.},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {1244--1250},
year = {2005},
url = {https://ijcai.org/proceedings/2005/194},
}
TY - CPAPER TI - Planning with Continuous Resources in Stochastic Domains AU - Mausam AU - Benazera, Emmanuel AU - Brafman, Ronen I. AU - Meuleau, Nicolas AU - Hansen, Eric A. T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 1244 EP - 1250 UR - https://ijcai.org/proceedings/2005/194 ER -Copied
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