4 papers
Reinforcement Learning for Optimal Stopping in POMDPs with Application to Quickest Change Detection
Austin Cooper, Sean Meyn
The field of quickest change detection (QCD) focuses on the design and analysis of online algorithms that estimate the time at which a significant event occurs. In this paper, desi…
Predictive Machine Learning to Increase the Throughput of Container Yards
Austin Ford Cooper
This study seeks to improve the throughput rates for shipping container terminals. In the United States, shipping ports link the domestic economy to global markets and are vital to…
Reinforcement Learning Design for Quickest Change Detection
Austin Cooper, Sean Meyn
The field of quickest change detection (QCD) concerns design and analysis of algorithms to estimate in real time the time at which an important event takes place, and identify prop…
Quickest Change Detection Using Mismatched CUSUM
Austin Cooper, Sean Meyn
Quickest change detection concerns estimation of an unknown change time \(τ_a\) from a sequence of partial observations \(\{Y_k:k\ge 0\}\). We consider stopping rules of CUSUM form…