4 papers
Model-based Offline RL via Robust Value-Aware Model Learning with Implicitly Differentiable Adaptive Weighting
Zhongjian Qiao, Jiafei Lyu, Boxiang Lyu +3
Model-based offline reinforcement learning (RL) aims to enhance offline RL with a dynamics model that facilitates policy exploration. However, \textit{model exploitation} could occ…
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…
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…
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…