Handling Non-Local Dead-Ends in Agent Planning Programs
Abstract
We propose an approach to reason about agent planning programs with global information. Agent planning programs can be understood as a network of planning tasks, accommodating long-term goals, non-terminating behaviors, and interactive execution. We provide a technique that relies on reasoning about ``global" dead-ends and that can be incorporated to any planning-based approach to agent planning problems. In doing so, we also introduce the notion of online execution of such planning structures. We provide experimental evidence suggesting the technique yields significant benefits.
Cite
Text
Chrpa et al. "Handling Non-Local Dead-Ends in Agent Planning Programs." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/135Markdown
[Chrpa et al. "Handling Non-Local Dead-Ends in Agent Planning Programs." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/chrpa2017ijcai-handling/) doi:10.24963/IJCAI.2017/135BibTeX
@inproceedings{chrpa2017ijcai-handling,
title = {{Handling Non-Local Dead-Ends in Agent Planning Programs}},
author = {Chrpa, Lukás and Lipovetzky, Nir and Sardiña, Sebastian},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2017},
pages = {971-978},
doi = {10.24963/IJCAI.2017/135},
url = {https://mlanthology.org/ijcai/2017/chrpa2017ijcai-handling/}
}