Markov Decision Processes with Time-varying Transition Probabilities and Rewards

By Yingying Li, Aoxiao Zhong, Guannan Qu, Na Li. 2019

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Ruihao Zhu
2. David Simchi-Levi
3. Wang Chi Cheung
4. Ahmed Touati
5. Weichao Mao
6. Omar Darwiche Domingues

Citations in the corpus

• Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism (2020, background): “The authors of (Even-Dar et al., 2005; Yu & Mannor, 2009; Neu et al., 2012; Abbasi-Yadkori et al., 2013; Rosenberg & Mansour, 2019; Li et al., 2019) considered RL in non-stationary MDPs with full information feedback.”