Structured preferences: a literature survey

AV Karpov - Automation and Remote Control, 2022 - Springer
A survey of papers on practically significant restrictions on the preference profile of a
collective is carried out, including single-peaked preferences, group-separable preferences …

Learn to match with no regret: Reinforcement learning in markov matching markets

Y Min, T Wang, R Xu, Z Wang… - Advances in Neural …, 2022 - proceedings.neurips.cc
We study a Markov matching market involving a planner and a set of strategic agents on the
two sides of the market. At each step, the agents are presented with a dynamical context …

Learning equilibria in matching markets from bandit feedback

M Jagadeesan, A Wei, Y Wang… - Advances in …, 2021 - proceedings.neurips.cc
Large-scale, two-sided matching platforms must find market outcomes that align with user
preferences while simultaneously learning these preferences from data. But since …

Learning strategies in decentralized matching markets under uncertain preferences

X Dai, MI Jordan - Journal of Machine Learning Research, 2021 - jmlr.org
We study the problem of decision-making in the setting of a scarcity of shared resources
when the preferences of agents are unknown a priori and must be learned from data. Taking …

Decentralized learning in online queuing systems

F Sentenac, E Boursier… - Advances in Neural …, 2021 - proceedings.neurips.cc
Motivated by packet routing in computer networks, online queuing systems are composed of
queues receiving packets at different rates. Repeatedly, they send packets to servers, each …

Matching in multi-arm bandit with collision

Y Zhang, S Wang, Z Fang - Advances in Neural Information …, 2022 - proceedings.neurips.cc
In this paper, we consider the matching of multi-agent multi-armed bandit problem, ie, while
agents prefer arms with higher expected reward, arms also have preferences on agents. In …

Competing for shareable arms in multi-player multi-armed bandits

R Xu, H Wang, X Zhang, B Li… - … Conference on Machine …, 2023 - proceedings.mlr.press
Competitions for shareable and limited resources have long been studied with strategic
agents. In reality, agents often have to learn and maximize the rewards of the resources at …

Thompson sampling for bandit learning in matching markets

F Kong, J Yin, S Li - arXiv preprint arXiv:2204.12048, 2022 - arxiv.org
The problem of two-sided matching markets has a wide range of real-world applications and
has been extensively studied in the literature. A line of recent works have focused on the …

Player-optimal stable regret for bandit learning in matching markets

F Kong, S Li - Proceedings of the 2023 Annual ACM-SIAM …, 2023 - SIAM
The problem of matching markets has been studied for a long time in the literature due to its
wide range of applications. Finding a stable matching is a common equilibrium objective in …

Improved Bandits in Many-to-One Matching Markets with Incentive Compatibility

F Kong, S Li - Proceedings of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
Two-sided matching markets have been widely studied in the literature due to their rich
applications. Since participants are usually uncertain about their preferences, online …