When to Stop? That Is the Question

Shulamit Reches, Meir Kalech, Rami Stern

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


When to make a decision is a key question in decision making problems characterized by uncertainty. In this paper we deal with decision making in environments where the information arrives dynamically. We address the tradeoff between waiting and stopping strategies. On the one hand, waiting to obtain more information reduces the uncertainty, but it comes with a cost. On the other hand, stopping and making a decision based on an expected utility, decreases the cost of waiting, but the decision is made based on uncertain information. In this paper, we prove that computing the optimal time to make a decision that guarantees the optimal utility is NP-hard. We propose a pessimistic approximation that guarantees an optimal decision when the recommendation is to wait. We empirically evaluate our algorithm and show that the quality of the decision is near-optimal and much faster than the optimal algorithm.

Original languageEnglish
Title of host publicationProceedings of the 25th AAAI Conference on Artificial Intelligence, AAAI 2011
PublisherAAAI press
Number of pages6
ISBN (Electronic)9781577355083
StatePublished - 11 Aug 2011
Event25th AAAI Conference on Artificial Intelligence, AAAI 2011 - San Francisco, United States
Duration: 7 Aug 201111 Aug 2011

Publication series

NameProceedings of the 25th AAAI Conference on Artificial Intelligence, AAAI 2011


Conference25th AAAI Conference on Artificial Intelligence, AAAI 2011
Country/TerritoryUnited States
CitySan Francisco

ASJC Scopus subject areas

  • Artificial Intelligence


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