Multiagent resource allocation with sharable items

被引:0
|
作者
Stéphane Airiau
Ulle Endriss
机构
[1] Université Paris Dauphine,LAMSADE
[2] University of Amsterdam,Institute for Logic, Language, and Computation
关键词
Multiagent resource allocation; Congestion games;
D O I
暂无
中图分类号
学科分类号
摘要
We study a particular multiagent resource allocation problem with indivisible, but sharable resources. In our model, the utility of an agent for using a bundle of resources is the difference between the value the agent would assign to that bundle in isolation and a congestion cost that depends on the number of agents she has to share each of the resources in her bundle with. The valuation function determining the value and the delay function determining the congestion cost can be agent-dependent. When the agents that share a resource also share control over that resource, then the current users of a resource will require some compensation when a new agent wants to join them using the resource. For this scenario of shared control, we study the existence of distributed negotiation protocols that lead to a social optimum. Depending on constraints on the valuation functions (mainly modularity), on the delay functions (such as convexity), and on the structural complexity of the deals between agents, we prove either the existence of a sequences of deals leading to a social optimum or the convergence of all sequences of deals to such an optimum. We also analyse the length of the path leading to such optimal allocations. For scenarios where the agents using a resource do not have shared control over that resource (i.e., where any agent can use any resource she wants), we study the existence of pure Nash equilibria, i.e., allocations in which no single agent has an incentive to add or drop any of the resources she is currently holding. We provide results for modular valuation functions, we analyse the length of the paths leading to a pure Nash equilibrium, and we relate our findings to results from the literature on congestion games.
引用
收藏
页码:956 / 985
页数:29
相关论文
共 50 条
  • [31] On the Dual Gradient Descent Method for the Resource Allocation Problem in Multiagent Systems
    D. B. Rokhlin
    [J]. Journal of Applied and Industrial Mathematics, 2024, 18 (2) : 316 - 332
  • [32] Distributed optimal resource allocation of second-order multiagent systems
    Deng, Zhenhua
    Liang, Shu
    Yu, Weiyong
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2018, 28 (14) : 4246 - 4260
  • [33] Computational complexity and approximability of social welfare optimization in multiagent resource allocation
    Nhan-Tam Nguyen
    Trung Thanh Nguyen
    Roos, Magnus
    Rothe, Joerg
    [J]. AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2014, 28 (02) : 256 - 289
  • [34] Distributed resource allocation of second-order nonlinear multiagent systems
    Li, Shiling
    Nian, Xiaohong
    Deng, Zhenhua
    Chen, Zhao
    Meng, Qing
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2021, 31 (11) : 5330 - 5342
  • [35] Minimising inequality in multiagent resource allocation Structural analysis of a distributed approach
    Schneckenburger, Sebastian
    Dorn, Britta
    Endriss, Ulle
    [J]. ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE, 2022, 90 (04) : 339 - 371
  • [36] Resource Allocation with Multi-Unit Items: Representation and Computational Results
    Dang Nguyen Le
    Ngoc-Khuong Nguyen
    Trung Thanh Nguyen
    [J]. 2017 4TH NAFOSTED CONFERENCE ON INFORMATION AND COMPUTER SCIENCE (NICS), 2017, : 60 - 65
  • [37] Sharing is Caring: Multiprocessor Scheduling with a Sharable Resource
    Kling, Peter
    Maecker, Alexander
    Riechers, Soeren
    Skopalik, Alexander
    [J]. PROCEEDINGS OF THE 29TH ACM SYMPOSIUM ON PARALLELISM IN ALGORITHMS AND ARCHITECTURES (SPAA'17), 2017, : 123 - 132
  • [38] A survey of approximability and inapproximability results for social welfare optimization in multiagent resource allocation
    Trung Thanh Nguyen
    Roos, Magnus
    Rothe, Joerg
    [J]. ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE, 2013, 68 (1-3) : 65 - 90
  • [39] Multiagent resource allocation in k-additive domains:: preference representation and complexity
    Chevaleyre, Yann
    Endriss, Ulle
    Estivie, Sylvia
    Maudet, Nicolas
    [J]. ANNALS OF OPERATIONS RESEARCH, 2008, 163 (01) : 49 - 62
  • [40] Decentralized Resource Allocation-Based Multiagent Deep Learning in Vehicular Network
    Mafuta, Armeline D.
    Maharaj, Bodhaswar T. J.
    Alfa, Attahiru S.
    [J]. IEEE SYSTEMS JOURNAL, 2023, 17 (01): : 87 - 98