11 papers
A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design
Rui Ai, Boxiang Lyu, Zhaoran Wang +2
We study reserve price optimization in multi-phase second price auctions, where the seller's prior actions affect the bidders' later valuations through a Markov Decision Process (M…
The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability
Jiachen Hu, Rui Ai, Han Zhong +4
Information asymmetry is a pervasive feature of multi-agent systems, especially evident in economics and social sciences. In these settings, agents tailor their actions based on pr…
Policy learning "without" overlap: Pessimism and generalized empirical Bernstein's inequality
Ying Jin, Zhimei Ren, Zhuoran Yang +1
This paper studies offline policy learning, which aims at utilizing observations collected a priori (from either fixed or adaptively evolving behavior policies) to learn an optimal…
An Instrumental Value for Data Production and its Application to Data Pricing
Rui Ai, Boxiang Lyu, Zhaoran Wang +2
How much value does a dataset or a data production process have to an agent who wishes to use the data to assist decision-making? This is a fundamental question towards understandi…
Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs
Han Zhong, Zhongren Chen, Zhuoran Yang +2
We study episodic reinforcement learning (RL) in non-stationary linear kernel Markov decision processes (MDPs). In this setting, both the reward function and the transition kernel…
Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach
Shuang Qiu, Boxiang Lyu, Qinglin Meng +3
Dynamic mechanism design studies how mechanism designers should allocate resources among agents in a time-varying environment. We consider the problem where the agents interact wit…