Backward Q-learning: The combination of Sarsa algorithm and Q-learning
By Yin-Hao Wang, Tzuu-Hseng S. Li, Chih-Jui Lin. 2013
160 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Reinforcement Learning
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sergey Levine
- Alex Smola
- Pieter Abbeel
- Pratik Chaudhari
- Yoshua Bengio
- Brendan O'Donoghue
- R´emi Munos
- Ruslan Salakhutdinov
In Reinforcement Learning
- Sergey Levine
- Brendan O'Donoghue
- Pratik Chaudhari
- Alex Smola
- Rasool Fakoor
- Pieter Abbeel
- R´emi Munos
- Volodymyr Mnih
Citations in the corpus
- PGQ: Combining policy gradient and Q-learning (2016, background): “Other works have attempted to combine on and off-policy learning, primarily using action-value fitting methods (Wang et al., 2013; Hausknecht & Stone, 2016; Lehnert & Precup, 2015), with varying degrees of success.”
- P3O: Policy-on Policy-off Policy Optimization (2019, background): “Let us note there are a number of works that learn action value functions using off-policy data, e.g.,Wang et al. (2013); Hausknecht and Stone (2016); Lehnert and Precup (2015) that achieve varying degrees of success on reinforcement learning benchmarks.”