mlsanityData to 7 Oct 2026

Intelligent Agents for Auction-based Federated Learning: A Survey

arXiv 2404.13244 ↗First posted 20 Apr 2024cs.LG cs.GTcited by 4

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Abstract (arXiv)

Auction-based federated learning (AFL) is an important emerging category of FL incentive mechanism design, due to its ability to fairly and efficiently motivate high-quality data owners to join data consumers' (i.e., servers') FL training tasks. To enhance the efficiency in AFL decision support for stakeholders (i.e., data consumers, data owners, and the auctioneer), intelligent agent-based techniques have emerged. However, due to the highly interdisciplinary nature of this field and the lack of a comprehensive survey providing an accessible perspective, it is a challenge for researchers to enter and contribute to this field. This paper bridges this important gap by providing a first-of-its-kind survey on the Intelligent Agents for AFL (IA-AFL) literature. We propose a unique multi-tiered taxonomy that organises existing IA-AFL works according to 1) the stakeholders served, 2) the auction mechanism adopted, and 3) the goals of the agents, to provide readers with a multi-perspective view into this field. In addition, we analyse the limitations of existing approaches, summarise the commonly adopted performance evaluation metrics, and discuss promising future directions leading towards effective and efficient stakeholder-oriented decision support in IA-AFL ecosystems.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 32 of its 72 references that are in the map. First posted on arXiv 20 Apr 2024.

Builds on

32 of 72 references.

References · 32

  1. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,592
  2. 2019Advances and Open Problems in Federated Learningcited by 3,021
  3. 2018Federated Learning with Non-IID Datacited by 1,099
  4. 2016Federated Optimization: Distributed Machine Learning for On-Device Intelligencecited by 558
  5. 2020Threats to Federated Learning: A Surveycited by 171
  6. 2020FedVision: An Online Visual Object Detection Platform Powered by Federated Learningcited by 121
  7. 2018Blockchained On-Device Federated Learningcited by 105
  8. 2019Reliable Federated Learning for Mobile Networkscited by 92
  9. 2019Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanismcited by 75
  10. 2021GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learningcited by 73
  11. 2020FMore: An Incentive Scheme of Multi-dimensional Auction for Federated Learning in MECcited by 48
  12. 2021Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspectivecited by 47
20 more
  1. 2020An Incentive Mechanism for Federated Learning in Wireless Cellular network: An Auction Approachcited by 39
  2. 2019Toward an Automated Auction Framework for Wireless Federated Learning Services Marketcited by 38
  3. 2021A Comprehensive Survey of Incentive Mechanism for Federated Learningcited by 38
  4. 2020Learning in repeated auctionscited by 15
  5. 2023Fairness-Aware Client Selection for Federated Learningcited by 15
  6. 2020Joint Auction-Coalition Formation Framework for Communication-Efficient Federated Learning in UAV-Enabled Internet of Vehiclescited by 14
  7. 2020A VCG-based Fair Incentive Mechanism for Federated Learningcited by 11
  8. 2023Towards Interpretable Federated Learningcited by 11
  9. 2021Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networkscited by 10
  10. 2023Utility-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learningcited by 7
  11. 2022Online Auction-Based Incentive Mechanism Design for Horizontal Federated Learning with Budget Constraintcited by 6
  12. 2022Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurementcited by 5
  13. 2023BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learningcited by 5
  14. 2020Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learningcited by 4
  15. 2022Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioningcited by 4
  16. 2023Multi-Tier Client Selection for Mobile Federated Learning Networkscited by 3
  17. 2023Multi-Session Budget Optimization for Forward Auction-based Federated Learningcited by 3
  18. 2020Optimal Procurement Auction for Cooperative Production of Virtual Products: Vickrey-Clarke-Groves Meet Cremer-McLeancited by 2
  19. 2021Applications of Auction and Mechanism Design in Edge Computing: A Surveycited by 2
  20. 2023Hire When You Need to: Gradual Participant Recruitment for Auction-based Federated Learningcited by 1

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Cited by year

Citing papers per year: 2024: 1; 2025: 3.

4 papers.

  1. 2024Advances and Open Challenges in Federated Foundation Modelscited by 33
  2. 2025Ten Challenging Problems in Federated Foundation Modelscited by 20
  3. 2025Incentive-Based Federated Learning: Architectural Elements and Future Directionscited by 1
  4. 2025Gaming and Cooperation in Federated Learning: What Can Happen and How to Monitor Itcited by 0