---
_id: '7402'
abstract:
- lang: eng
text: Graph planning gives rise to fundamental algorithmic questions such as shortest
path, traveling salesman problem, etc. A classical problem in discrete planning
is to consider a weighted graph and construct a path that maximizes the sum of
weights for a given time horizon T. However, in many scenarios, the time horizon
is not fixed, but the stopping time is chosen according to some distribution such
that the expected stopping time is T. If the stopping time distribution is not
known, then to ensure robustness, the distribution is chosen by an adversary,
to represent the worst-case scenario. A stationary plan for every vertex always
chooses the same outgoing edge. For fixed horizon or fixed stopping-time distribution,
stationary plans are not sufficient for optimality. Quite surprisingly we show
that when an adversary chooses the stopping-time distribution with expected stopping
time T, then stationary plans are sufficient. While computing optimal stationary
plans for fixed horizon is NP-complete, we show that computing optimal stationary
plans under adversarial stopping-time distribution can be achieved in polynomial
time. Consequently, our polynomial-time algorithm for adversarial stopping time
also computes an optimal plan among all possible plans.
article_processing_charge: No
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Laurent
full_name: Doyen, Laurent
last_name: Doyen
citation:
ama: 'Chatterjee K, Doyen L. Graph planning with expected finite horizon. In: *34th
Annual ACM/IEEE Symposium on Logic in Computer Science*. IEEE; 2019:1-13. doi:10.1109/lics.2019.8785706'
apa: 'Chatterjee, K., & Doyen, L. (2019). Graph planning with expected finite
horizon. In *34th Annual ACM/IEEE Symposium on Logic in Computer Science*
(pp. 1–13). Vancouver, BC, Canada: IEEE. https://doi.org/10.1109/lics.2019.8785706'
chicago: Chatterjee, Krishnendu, and Laurent Doyen. “Graph Planning with Expected
Finite Horizon.” In *34th Annual ACM/IEEE Symposium on Logic in Computer Science*,
1–13. IEEE, 2019. https://doi.org/10.1109/lics.2019.8785706.
ieee: K. Chatterjee and L. Doyen, “Graph planning with expected finite horizon,”
in *34th Annual ACM/IEEE Symposium on Logic in Computer Science*, Vancouver,
BC, Canada, 2019, pp. 1–13.
ista: 'Chatterjee K, Doyen L. 2019. Graph planning with expected finite horizon.
34th Annual ACM/IEEE Symposium on Logic in Computer Science. LICS: Symposium on
Logic in Computer Science, 1–13.'
mla: Chatterjee, Krishnendu, and Laurent Doyen. “Graph Planning with Expected Finite
Horizon.” *34th Annual ACM/IEEE Symposium on Logic in Computer Science*,
IEEE, 2019, pp. 1–13, doi:10.1109/lics.2019.8785706.
short: K. Chatterjee, L. Doyen, in:, 34th Annual ACM/IEEE Symposium on Logic in
Computer Science, IEEE, 2019, pp. 1–13.
conference:
end_date: 2019-06-27
location: Vancouver, BC, Canada
name: 'LICS: Symposium on Logic in Computer Science'
start_date: 2019-06-24
date_created: 2020-01-29T16:18:33Z
date_published: 2019-06-01T00:00:00Z
date_updated: 2021-01-12T08:13:25Z
day: '01'
department:
- _id: KrCh
doi: 10.1109/lics.2019.8785706
external_id:
arxiv:
- '1802.03642'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1802.03642
month: '06'
oa: 1
oa_version: Preprint
page: 1-13
publication: 34th Annual ACM/IEEE Symposium on Logic in Computer Science
publication_identifier:
isbn:
- '9781728136080'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: 1
status: public
title: Graph planning with expected finite horizon
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2019'
...