mlsanityData to 14 Oct 2026

Average-Reward Maximum Entropy Reinforcement Learning for Global Policy in Double Pendulum Tasks

arXiv 2505.07516 ↗First posted 12 May 2025cs.ROcited by 0

On the map: Deep reinforcement learning methods → RL theory and sample complexity

Abstract (arXiv)

This report presents our reinforcement learning-based approach for the swing-up and stabilisation tasks of the acrobot and pendubot, tailored specifcially to the updated guidelines of the 3rd AI Olympics at ICRA 2025. Building upon our previously developed Average-Reward Entropy Advantage Policy Optimization (AR-EAPO) algorithm, we refined our solution to effectively address the new competition scenarios and evaluation metrics. Extensive simulations validate that our controller robustly manages these revised tasks, demonstrating adaptability and effectiveness within the updated framework.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL theory and sample complexity, one of 15 directions in Deep reinforcement learning methods. Builds on 7 of its 11 references that are in the map. First posted on arXiv 12 May 2025.

Builds on

7 of 11 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024Velocity-History-Based Soft Actor-Critic Tackling IROS'24 Competition "AI Olympics with RealAIGym"26 Oct
  2. 2024Average-Reward Maximum Entropy Reinforcement Learning for Underactuated Double Pendulum Tasks13 Sep
  3. 2024Learning control of underactuated double pendulum with Model-Based Reinforcement Learning9 Sep

Other references · 4

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2015High-Dimensional Continuous Control Using Generalized Advantage Estimationcited by 2,026
  3. 2024AI Olympics challenge with Evolutionary Soft Actor Criticcited by 2
  4. 2025Reinforcement Learning for Robust Athletic Intelligence: Lessons from the 2nd 'AI Olympics with RealAIGym' Competitioncited by 2

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Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2024Maximum Entropy On-Policy Actor-Critic via Entropy Advantage Estimation
  2. 2025Entropy-Controlled Intrinsic Motivation Reinforcement Learning for Quadruped Robot Locomotion in Complex Terrains
  3. 2022Weighted Maximum Entropy Inverse Reinforcement Learning
  4. 2025Learning global control of underactuated systems with Model-Based Reinforcement Learning
  5. 2026FERPO: Forward Entropy-Regularized Policy Optimization
  6. 2020Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms
  7. 2025Statistical analysis of Inverse Entropy-regularized Reinforcement Learning
  8. 2025Trajectory Entropy Reinforcement Learning for Robust Robot Motor Skill Learning