mlsanityData to 14 Oct 2026

Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems

arXiv 2212.07313 ↗First posted 14 Dec 2022cs.LG cs.MA cs.SYcited by 18

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Abstract (arXiv)

We consider the sequential decision-making problem of making proactive request assignment and rejection decisions for a profit-maximizing operator of an autonomous mobility on demand system. We formalize this problem as a Markov decision process and propose a novel combination of multi-agent Soft Actor-Critic and weighted bipartite matching to obtain an anticipative control policy. Thereby, we factorize the operator's otherwise intractable action space, but still obtain a globally coordinated decision. Experiments based on real-world taxi data show that our method outperforms state of the art benchmarks with respect to performance, stability, and computational tractability.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Builds on 15 of its 28 references that are in the map. First posted on arXiv 14 Dec 2022.

Builds on

15 of 28 references.

References · 15

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  3. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,558
  4. 2018Actor-Attention-Critic for Multi-Agent Reinforcement Learningcited by 261
  5. 2019Soft Actor-Critic for Discrete Action Settingscited by 174
  6. 2022In Defense of the Unitary Scalarization for Deep Multi-Task Learningcited by 67
  7. 2019Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learningcited by 57
  8. 2021A Deep Value-network Based Approach for Multi-Driver Order Dispatchingcited by 45
  9. 2019Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problemcited by 29
  10. 2021Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systemscited by 28
  11. 2019Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matchingcited by 26
  12. 2014Control of Robotic Mobility-On-Demand Systems: a Queueing-Theoretical Perspectivecited by 25
3 more
  1. 2021Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learningcited by 22
  2. 2022Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplacecited by 11
  3. 2021A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problemcited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 5; 2024: 3; 2025: 7; 2026: 3.

18 papers.

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  1. 2023Learning-based Online Optimization for Autonomous Mobility-on-Demand Fleet Controlcited by 14
  2. 2023Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systemscited by 8
  3. 2025BMG-Q: Localized Bipartite Match Graph Attention Q-Learning for Ride-Pooling Order Dispatchcited by 7
  4. 2025Structured Reinforcement Learning for Combinatorial Decision-Makingcited by 7
  5. 2024Risk-Sensitive Soft Actor-Critic for Robust Deep Reinforcement Learning under Distribution Shiftscited by 6
  6. 2024Stochastic Q-learning for Large Discrete Action Spacescited by 5
  7. 2025One Step is Enough: Multi-Agent Reinforcement Learning based on One-Step Policy Optimization for Order Dispatch on Ride-Sharing Platformscited by 5
  8. 2023Dynamic Neighborhood Construction for Structured Large Discrete Action Spacescited by 4
  9. 2025CoDriveVLM: VLM-Enhanced Urban Cooperative Dispatching and Motion Planning for Future Autonomous Mobility on Demand Systemscited by 4
  10. 2025Triple-BERT: Do We Really Need MARL for Order Dispatch on Ride-Sharing Platforms?cited by 4
  11. 2024Multi-Agent Soft Actor-Critic with Coordinated Loss for Autonomous Mobility-on-Demand Fleet Controlcited by 3
  12. 2025Coordinating Ride-Pooling with Public Transit using Reward-Guided Conservative Q-Learning: An Offline Training and Online Fine-Tuning Reinforcement Learning Frameworkcited by 3
6 more
  1. 2026Combinatorial Optimization Augmented Machine Learningcited by 3
  2. 2023Surge Routing: Event-informed Multiagent Reinforcement Learning for Autonomous Ridesharecited by 1
  3. 2023Approximate Multiagent Reinforcement Learning for On-Demand Urban Mobility Problem on a Large Map (extended version)cited by 1
  4. 2025Atomic Proximal Policy Optimization for Electric Robo-Taxi Dispatch and Charger Allocationcited by 1
  5. 2026RideSkill: A Hierarchical Algorithm for Generalized Ride Sharing with LLM-Driven Automatic Evolutioncited by 0
  6. 2026Synergizing Drone Delivery Order Pooling and Road Network Monitoring through Monitoring-Task Orderizationcited by 0