Dual Temporal Difference Learning

By Min Yang, Yuxi Li, Dale Schuurmans. 2009

5 citations recorded by the source corpus.

How researchers see this paper

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

1. Mengdi Wang
2. Yichen Chen
3. Lihong Li
4. Ofir Nachum
5. Bo Dai
6. Ziyang Tang
7. Nan Jiang
8. Donghwan Lee

Citations in the corpus

• Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement Learning (2016, background): “Now we are ready to present the sample complexity of SPD for discounted MDP. Theorem 4 shows that the averaged dual iterate λ̂ gives a randomized policy that approximates the optimal policy π∗.”
• Scalable Bilinear π Learning Using State and Action Features (2018, methodology): “Previous work also uses linear approximation of value functions (Bertsekas & Tsitsiklis, 1996; Elkan, 2011), or state transition probabilities (Wang et al., 2007; Yang et al., 2009).”
• An online primal-dual method for discounted Markov decision processes (2016, background): “In the RL literatures, there have been some works about dual temporal difference learning and primaldual methods, see for examples [13], [15], [16], [24].”