147 citations · 384 across the 17 of their papers we have counts for
3 papers · 1 filter
Distributional constrained reinforcement learning for supply chain optimization
Jaime Sabal Bermúdez, Antonio del Rio Chanona, Calvin Tsay
This work studies reinforcement learning (RL) in the context of multi-period supply chains subject to constraints, e.g., on production and inventory. We introduce Distributional Co…
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization
Jose Pablo Folch, Robert M Lee, Behrang Shafei +4
Bayesian Optimization is a useful tool for experiment design. Unfortunately, the classical, sequential setting of Bayesian Optimization does not translate well into laboratory expe…
SnAKe: Bayesian Optimization with Pathwise Exploration
Jose Pablo Folch, Shiqiang Zhang, Robert M Lee +5
Bayesian Optimization is a very effective tool for optimizing expensive black-box functions. Inspired by applications developing and characterizing reaction chemistry using droplet…