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Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

arXiv 1810.06394 ↗First posted 10 Oct 2018cs.LG cs.AI stat.MLcited by 54

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Abstract (arXiv)

Most existing deep reinforcement learning (DRL) frameworks consider either discrete action space or continuous action space solely. Motivated by applications in computer games, we consider the scenario with discrete-continuous hybrid action space. To handle hybrid action space, previous works either approximate the hybrid space by discretization, or relax it into a continuous set. In this paper, we propose a parametrized deep Q-network (P- DQN) framework for the hybrid action space without approximation or relaxation. Our algorithm combines the spirits of both DQN (dealing with discrete action space) and DDPG (dealing with continuous action space) by seamlessly integrating them. Empirical results on a simulation example, scoring a goal in simulated RoboCup soccer and the solo mode in game King of Glory (KOG) validate the efficiency and effectiveness of our method.

Key facts. Cited by 54 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Oct 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2020: 1; 2021: 8; 2022: 7; 2023: 7; 2024: 7; 2025: 14; 2026: 10.

54 papers.

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  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. 2021Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domaincited by 57
  4. 2020Deep Imitation Learning for Bimanual Robotic Manipulationcited by 49
  5. 2021HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representationcited by 33
  6. 2023HACMan: Learning Hybrid Actor-Critic Maps for 6D Non-Prehensile Manipulationcited by 27
  7. 2021ReLAX: Reinforcement Learning Agent eXplainer for Arbitrary Predictive Modelscited by 25
  8. 2021Survey of Recent Multi-Agent Reinforcement Learning Algorithms Utilizing Centralized Trainingcited by 16
  9. 2021Automated Synthesis of Steady-State Continuous Processes using Reinforcement Learningcited by 10
  10. 2024RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuningcited by 9
  11. 2022Meta-Learning Parameterized Skillscited by 7
  12. 2024Model-based Reinforcement Learning for Parameterized Action Spacescited by 7
38 more
  1. 2022Reinforcement learning for traffic signal control in hybrid action spacecited by 5
  2. 2024HACMan++: Spatially-Grounded Motion Primitives for Manipulationcited by 5
  3. 2021Design Strategy Network: A deep hierarchical framework to represent generative design strategies in complex action spacescited by 4
  4. 2023Counter-Empirical Attacking based on Adversarial Reinforcement Learning for Time-Relevant Scoring Systemcited by 3
  5. 2022Learning-Based Client Selection for Federated Learning Services Over Wireless Networks with Constrained Monetary Budgetscited by 2
  6. 2023Optimal Scheduling in IoT-Driven Smart Isolated Microgrids Based on Deep Reinforcement Learningcited by 2
  7. 2025A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspectivecited by 2
  8. 2025Multi-Functional RIS-Enabled in SAGIN for IoT: A Hybrid Deep Reinforcement Learning Approach with Compressed Twin-Modelscited by 2
  9. 2022Collaborative Intelligent Reflecting Surface Networks with Multi-Agent Reinforcement Learningcited by 1
  10. 2023Diverse Policy Optimization for Structured Action Spacecited by 1
  11. 2024CycLight: learning traffic signal cooperation with a cycle-level strategycited by 1
  12. 2024Constrained Optimal Fuel Consumption of HEV: A Constrained Reinforcement Learning Approachcited by 1
  13. 2024Detecting Continuous Integration Skip : A Reinforcement Learning-based Approachcited by 1
  14. 2025Learning Parameterized Skills from Demonstrationscited by 1
  15. 2025Logic-informed reinforcement learning for cross-domain optimization of large-scale cyber-physical systemscited by 1
  16. 2026Parametrized Sharing for Multi-Agent Hybrid DRL for Multiple Multi-Functional RISs-Aided Downlink NOMA Networkscited by 1
  17. 2026Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradientscited by 1
  18. 2022Joint Energy Dispatch and Unit Commitment in Microgrids Based on Deep Reinforcement Learningcited by 0
  19. 2022Eco-driving for Electric Connected Vehicles at Signalized Intersections: A Parameterized Reinforcement Learning approachcited by 0
  20. 2022Computational Discovery of Energy-Efficient Heat Treatment for Microstructure Design using Deep Reinforcement Learningcited by 0
  21. 2023Mixed-Integer Optimal Control via Reinforcement Learning: A Case Study on Hybrid Electric Vehicle Energy Managementcited by 0
  22. 2023Integrating Renewable Energy in Agriculture: A Deep Reinforcement Learning-based Approachcited by 0
  23. 2023Learning impartial policies for sequential counterfactual explanations using Deep Reinforcement Learningcited by 0
  24. 2024Scheduling Drone and Mobile Charger via Hybrid-Action Deep Reinforcement Learningcited by 0
  25. 2025Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processescited by 0
  26. 2025Multi-Agent Deep Reinforcement Learning for Safe Autonomous Driving with RICS-Assisted MECcited by 0
  27. 2025Distributions as Actions: A Unified Framework for Diverse Action Spacescited by 0
  28. 2025Multi-Timescale Hierarchical Reinforcement Learning for Unified Behavior and Control of Autonomous Drivingcited by 0
  29. 2025Strategic Communication under Threat: Learning Information Trade-offs in Pursuit-Evasion Gamescited by 0
  30. 2025Learning to Drive Safely with Hybrid Optionscited by 0
  31. 2025Energy-Efficient Autonomous Driving with Adaptive Perception and Robust Decisioncited by 0
  32. 2025Hybrid DQN-TD3 Reinforcement Learning for Autonomous Navigation in Dynamic Environmentscited by 0
  33. 2025FM-EAC: Feature Model-based Enhanced Actor-Critic for Multi-Task Control in Dynamic Environmentscited by 0
  34. 2025Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actionscited by 0
  35. 2026CHDP: Cooperative Hybrid Diffusion Policies for Reinforcement Learning in Parameterized Action Spacecited by 0
  36. 2026Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spacescited by 0
  37. 2026Temporal Action Representation Learning for Tactical Resource Control and Subsequent Maneuver Generationcited by 0
  38. 2026PALCAS: A Priority-Aware Intelligent Lane Change Advisory System for Autonomous Vehicles using Federated Reinforcement Learningcited by 0

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