Modeling recommender ecosystems: Research challenges at the intersection of mechanism design, reinforcement learning and generative models
C Boutilier, M Mladenov, G Tennenholtz - ar** insert-eliminate algorithm for multi-agent bandits
We consider a decentralized multi-agent Multi Armed Bandit (MAB) setup consisting of $ N $
agents, solving the same MAB instance to minimize individual cumulative regret. In our …
agents, solving the same MAB instance to minimize individual cumulative regret. In our …
Robust multi-agent multi-armed bandits
Recent works have shown that agents facing independent instances of a stochastic K-armed
bandit can collaborate to decrease regret. However, these works assume that each agent …
bandit can collaborate to decrease regret. However, these works assume that each agent …
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 …
when the preferences of agents are unknown a priori and must be learned from data. Taking …