Actor-citic agorithms

By Vijay R. Konda, John N. Tsitsiklis. 1999

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1. Sergey Levine
2. Shixiang Shane Gu
3. Pieter Abbeel
4. Yoshua Bengio
5. Chelsea Finn
6. Ruslan Salakhutdinov
7. Trevor Darrell
8. Ofir Nachum

Citations in the corpus

• A Function Approximation Approach to Estimation of Policy Gradient for POMDP with Structured Policies (2005, methodology): “We approximate the function v(y, u) or vβ(y, u) by φ(y, u)′r, where r is a vector of linear coefficients, to be computed by TD algorithms.5 The same as in MDP (Konda and Tsitsiklis, 1999), (Sutton et al., 1999), Eq.”
• Continuous Deep Q-Learning with Model-based Acceleration (2016, methodology): “For this reason, continuous domains are often tackled using actor-critic methods (Konda & Tsitsiklis, 1999; Hafner & Riedmiller, 2011; Silver et al., 2014; Lillicrap et al., 2016), where a separate parameterized “actor” policy π is learned in addition to the Q-function or value function “critic,”…”