mlsanityData to 7 Oct 2026

Hierarchical Approaches for Reinforcement Learning in Parameterized Action Space

arXiv 1810.09656 ↗First posted 23 Oct 2018cs.LG cs.AI stat.MLcited by 15

Not on the map. Why?

Abstract (arXiv)

We explore Deep Reinforcement Learning in a parameterized action space. Specifically, we investigate how to achieve sample-efficient end-to-end training in these tasks. We propose a new compact architecture for the tasks where the parameter policy is conditioned on the output of the discrete action policy. We also propose two new methods based on the state-of-the-art algorithms Trust Region Policy Optimization (TRPO) and Stochastic Value Gradient (SVG) to train such an architecture. We demonstrate that these methods outperform the state of the art method, Parameterized Action DDPG, on test domains.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Oct 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2020: 1; 2021: 7; 2022: 0; 2023: 3; 2024: 3; 2025: 0; 2026: 1.

15 papers.

Sort:

By area:

  1. 2021Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Taskscited by 75
  2. 2021Accelerating Robotic Reinforcement Learning via Parameterized Action Primitivescited by 63
  3. 2020Deep Imitation Learning for Bimanual Robotic Manipulationcited by 49
  4. 2021Hierarchical Skills for Efficient Explorationcited by 37
  5. 2021HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representationcited by 33
  6. 2021ReLAX: Reinforcement Learning Agent eXplainer for Arbitrary Predictive Modelscited by 25
  7. 2023Efficient XAI Techniques: A Taxonomic Surveycited by 14
  8. 2021SelectAugment: Hierarchical Deterministic Sample Selection for Data Augmentationcited by 10
  9. 2023Deep Reinforcement Learning for Autonomous Cyber Defence: A Surveycited by 6
  10. 2021One model Packs Thousands of Items with Recurrent Conditional Query Learningcited by 5
  11. 2024Understanding What Affects the Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidencecited by 5
  12. 2024A semi-centralized multi-agent RL framework for efficient irrigation schedulingcited by 2
3 more
  1. 2023Diverse Policy Optimization for Structured Action Spacecited by 1
  2. 2024Simplex Decomposition for Portfolio Allocation Constraints in Reinforcement Learningcited by 1
  3. 2026Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spacescited by 0