9 citations · 12 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 3 cited
Periodic-GP: Learning Periodic World with Gaussian Process Bandits
Hengrui Cai, Zhihao Cen, Ling Leng +1
We consider the sequential decision optimization on the periodic environment, that occurs in a wide variety of real-world applications when the data involves seasonality, such as t…
stat.ML2020★ 9 cited
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making
Chengchun Shi, Runzhe Wan, Rui Song +2
The Markov assumption (MA) is fundamental to the empirical validity of reinforcement learning. In this paper, we propose a novel Forward-Backward Learning procedure to test MA in s…