mlsanityData to 7 Oct 2026

Model-based Reinforcement Learning for Parameterized Action Spaces

arXiv 2404.03037 ↗First posted 3 Apr 2024cs.LG cs.AIcited by 7

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Abstract (arXiv)

We propose a novel model-based reinforcement learning algorithm -- Dynamics Learning and predictive control with Parameterized Actions (DLPA) -- for Parameterized Action Markov Decision Processes (PAMDPs). The agent learns a parameterized-action-conditioned dynamics model and plans with a modified Model Predictive Path Integral control. We theoretically quantify the difference between the generated trajectory and the optimal trajectory during planning in terms of the value they achieved through the lens of Lipschitz Continuity. Our empirical results on several standard benchmarks show that our algorithm achieves superior sample efficiency and asymptotic performance than state-of-the-art PAMDP methods.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 38 of its 50 references that are in the map. First posted on arXiv 3 Apr 2024.

Builds on

38 of 50 references.

References · 38

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26 more
  1. 2019Model-Based Reinforcement Learning for Ataricited by 495
  2. 2022Temporal Difference Learning for Model Predictive Controlcited by 375
  3. 2020Planning to Explore via Self-Supervised World Modelscited by 365
  4. 2018Maximum a Posteriori Policy Optimisationcited by 318
  5. 2017Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuningcited by 288
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  15. 2018Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Spacecited by 54
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  17. 2019Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Spacecited by 53
  18. 2020Continuous-Discrete Reinforcement Learning for Hybrid Control in Roboticscited by 42
  19. 2019Variational Inference MPC for Bayesian Model-based Reinforcement Learningcited by 39
  20. 2021HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representationcited by 33
  21. 2017Robust and Efficient Transfer Learning with Hidden-Parameter Markov Decision Processescited by 28
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 3.

7 papers.

  1. 2025Knowledge Retention for Continual Model-Based Reinforcement Learningcited by 6
  2. 2025Near-Optimal Second-Order Guarantees for Model-Based Adversarial Imitation Learningcited by 2
  3. 2025Learning Parameterized Skills from Demonstrationscited by 1
  4. 2025Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processescited by 0
  5. 2026CHDP: Cooperative Hybrid Diffusion Policies for Reinforcement Learning in Parameterized Action Spacecited by 0
  6. 2026Transferable Delay-Aware Reinforcement Learning via Implicit Causal Graph Modelingcited by 0
  7. 2026From Noise to Control: Parameterized Diffusion Policiescited by 0