most citedWeakly Coupled Deep Q-Networks

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cs.LG2024

AExGym: Benchmarks and Environments for Adaptive Experimentation

Jimmy Wang, Ethan Che, Daniel R. Jiang +1

Innovations across science and industry are evaluated using randomized trials (a.k.a. A/B tests). While simple and robust, such static designs are inefficient or infeasible for tes…

cs.LG2023★ 1 cited

Weakly Coupled Deep Q-Networks

Ibrahim El Shar, Daniel R. Jiang

We propose weakly coupled deep Q-networks (WCDQN), a novel deep reinforcement learning algorithm that enhances performance in a class of structured problems called weakly coupled M…