TY - GEN
T1 - Online algorithms for multi-shop ski rental with machine learned predictions
AU - Wang, Shufan
AU - Li, Jian
N1 - Publisher Copyright:
© 2020 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). All rights reserved.
PY - 2020
Y1 - 2020
N2 - Uncertainty plays a critical role in many real world applications where the decision maker is faced with multiple alternatives with different costs. These decisions arise in our daily lives, such as whether to rent an apartment or buy a house, which cannot be answered reliably without knowledge of the future. These decision-making problems are usually modeled as online rent-or-buy problems, such as the classical ski rental problem [4, 5, 8]. Two paradigms have been widely studied to deal with such uncertainty. On the one hand, online algorithms are designed without prior knowledge to the problem, and competitive ratio (CR) is used to characterize the goodness of the algorithm in lack of the future. On the other hand, machine learning is applied to address uncertainty by making future predictions via building robust models on prior data.
AB - Uncertainty plays a critical role in many real world applications where the decision maker is faced with multiple alternatives with different costs. These decisions arise in our daily lives, such as whether to rent an apartment or buy a house, which cannot be answered reliably without knowledge of the future. These decision-making problems are usually modeled as online rent-or-buy problems, such as the classical ski rental problem [4, 5, 8]. Two paradigms have been widely studied to deal with such uncertainty. On the one hand, online algorithms are designed without prior knowledge to the problem, and competitive ratio (CR) is used to characterize the goodness of the algorithm in lack of the future. On the other hand, machine learning is applied to address uncertainty by making future predictions via building robust models on prior data.
UR - https://www.scopus.com/pages/publications/85096674994
M3 - Conference contribution
AN - SCOPUS:85096674994
T3 - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
SP - 2035
EP - 2037
BT - Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
A2 - An, Bo
A2 - El Fallah Seghrouchni, Amal
A2 - Sukthankar, Gita
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
T2 - 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
Y2 - 19 May 2020
ER -