3 papers
cs.MA2024
Data Poisoning to Fake a Nash Equilibrium in Markov Games
Young Wu, Jeremy McMahan, Xiaojin Zhu +1
We characterize offline data poisoning attacks on Multi-Agent Reinforcement Learning (MARL), where an attacker may change a data set in an attempt to install a (potentially fictiti…
cs.LG2024
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
Brahma S. Pavse, Matthew Zurek, Yudong Chen +2
In many reinforcement learning (RL) applications, we want policies that reach desired states and then keep the controlled system within an acceptable region around the desired stat…
stat.ML2024
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits
Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna +1
In this paper, we study the problem of optimal data collection for policy evaluation in linear bandits. In policy evaluation, we are given a target policy and asked to estimate the…