5 papers
Decentralized Multi-Player Q-Learning in Episodic Markov Decision Processes with Information Asymmetry
Larissa Xu, King Bi, William Chang
We study decentralized multi-player reinforcement learning in episodic tabular Markov decision processes (MDPs) under three forms of information asymmetry: (A) unobserved actions w…
Self-similar Delone sets and Pisot numbers
Christoph Bandt, Yves Meyer
We consider Delone point patterns with self-similarity. Under mild conditions, the similarity factor is a Pisot number if and only if the pattern is uniformly discrete. The classic…
Coordinating the Unknown Lipschitz Constant in Multiplayer Bandits
Ricardo Parada, Chenzhang Zhao, William Chang
Motivated by decentralized applications, we study cooperative multi-agent bandits in continuous (Lipschitz) action spaces when the Lipschitz constant is unknown. We consider three…
Multiplayer Information Asymmetric Contextual Bandits
William Chang, Yuanhao Lu
Single-player contextual bandits are a well-studied problem in reinforcement learning that has seen applications in various fields such as advertising, healthcare, and finance. In…
Multiplayer Information Asymmetric Bandits in Metric Spaces
William Chang, Aditi Karthik
In recent years the information asymmetric Lipschitz bandits In this paper we studied the Lipschitz bandit problem applied to the multiplayer information asymmetric problem studied…