TY - GEN
T1 - When to Stop? That Is the Question
AU - Reches, Shulamit
AU - Kalech, Meir
AU - Stern, Rami
N1 - Publisher Copyright:
Copyright © 2011, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2011/8/11
Y1 - 2011/8/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84899414411&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84899414411
T3 - Proceedings of the 25th AAAI Conference on Artificial Intelligence, AAAI 2011
SP - 1063
EP - 1068
BT - Proceedings of the 25th AAAI Conference on Artificial Intelligence, AAAI 2011
PB - AAAI press
T2 - 25th AAAI Conference on Artificial Intelligence, AAAI 2011
Y2 - 7 August 2011 through 11 August 2011
ER -