---
res:
bibo_abstract:
- 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.@eng
bibo_authorlist:
- foaf_Person:
foaf_givenName: Krishnendu
foaf_name: Chatterjee, Krishnendu
foaf_surname: Chatterjee
foaf_workInfoHomepage: http://www.librecat.org/personId=2E5DCA20-F248-11E8-B48F-1D18A9856A87
orcid: 0000-0002-4561-241X
- foaf_Person:
foaf_givenName: Laurent
foaf_name: Doyen, Laurent
foaf_surname: Doyen
bibo_doi: 10.1109/lics.2019.8785706
dct_date: 2019^xs_gYear
dct_isPartOf:
- http://id.crossref.org/issn/9781728136080
dct_language: eng
dct_publisher: IEEE@
dct_title: Graph planning with expected finite horizon@
...