Actor-Critic or Critic-Actor? A Tale of Two Time Scales
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Abstract (arXiv)
We revisit the standard formulation of tabular actor-critic algorithm as a two time-scale stochastic approximation with value function computed on a faster time-scale and policy computed on a slower time-scale. This emulates policy iteration. We observe that reversal of the time scales will in fact emulate value iteration and is a legitimate algorithm. We provide a proof of convergence and compare the two empirically with and without function approximation (with both linear and nonlinear function approximators) and observe that our proposed critic-actor algorithm performs on par with actor-critic in terms of both accuracy and computational effort.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 0 of its 27 references that are in the map. First posted on arXiv 10 Oct 2022.
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Citing papers per year: 2024: 2; 2025: 3; 2026: 2.
7 papers.
- 2024Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximationcited by 7
- 2025The Actor-Critic Update Order Matters for PPO in Federated Reinforcement Learningcited by 2
- 2024Reinforcement Learning with Quasi-Hyperbolic Discountingcited by 1
- 2025Convergent Reinforcement Learning Algorithms for Stochastic Shortest Path Problemcited by 0
- 2025Finite Time Analysis of Constrained Natural Critic-Actor Algorithm with Improved Sample Complexitycited by 0
- 2026Optimal Sample Complexity for Single Time-Scale Actor-Critic with Momentumcited by 0
- 2026A Concentration Bound for Two-Timescale Actor-Critic Algorithmcited by 0
- 2026A Concentration Bound for Two-Timescale Actor-Critic Algorithm24 Sep 2026
- 2026Optimal Sample Complexity for Single Time-Scale Actor-Critic with Momentum2 Feb 2026
- 2025Finite Time Analysis of Constrained Natural Critic-Actor Algorithm with Improved Sample Complexity5 Oct 2025
- 2025Convergent Reinforcement Learning Algorithms for Stochastic Shortest Path Problem19 Aug 2025
- 2025The Actor-Critic Update Order Matters for PPO in Federated Reinforcement Learning2 Jun 2025
- 2024Reinforcement Learning with Quasi-Hyperbolic Discounting16 Sep 2024
- 2024Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation2 Feb 2024