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Wei, Xupeng; Anastasopoulos, Achilleas

Mechanism design for demand management in energy communities. (English) Zbl 1484.91113

Games 12, No. 3, Paper No. 61, 34 p. (2021).

MSC:

91B03 Mechanism design theory
91B32 Resource and cost allocation (including fair division, apportionment, etc.)
91A26 Rationality and learning in game theory

Keywords:

mechanism design; Nash equilibrium; demand management; energy networks; learning in games
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References:

[1] Schmidt, D.A.; Shi, C.; Berry, R.A.; Honig, M.L.; Utschick, W.; Distributed resource allocation schemes; IEEE Signal Process. Mag.: 2009; Volume 26 ,53-63.
[2] Nair, A.S.; Hossen, T.; Campion, M.; Selvaraj, D.F.; Goveas, N.; Kaabouch, N.; Ranganathan, P.; Multi-agent systems for resource allocation and scheduling in a smart grid; Technol. Econ. Smart Grids Sustain. Energy: 2018; Volume 3 ,1-15.
[3] HamaAli, K.W.; Zeebaree, S.R.; Resources allocation for distributed systems: A review; Int. J. Sci. Bus.: 2021; Volume 5 ,76-88.
[4] Menache, I.; Ozdaglar, A.; Network games: Theory, models, and dynamics; Synth. Lect. Commun. Netw.: 2011; Volume 4 ,1-159. · Zbl 1304.91008
[5] Hurwicz, L.; Reiter, S.; ; Designing Economic Mechanisms: Cambridge, UK 2006; .
[6] Börgers, T.; Krahmer, D.; ; An Introduction to the Theory of Mechanism Design: Oxford, UK 2015; . · Zbl 1316.91001
[7] ; 2018 Smart Grid System Report: Washington, DC, USA 2018; .
[8] Garg, D.; Narahari, Y.; Gujar, S.; Foundations of mechanism design: A tutorial part 1-key concepts and classical results; Sadhana: 2008; Volume 33 ,83. · Zbl 1167.91353
[9] Garg, D.; Narahari, Y.; Gujar, S.; Foundations of mechanism design: A tutorial Part 2-Advanced concepts and results; Sadhana: 2008; Volume 33 ,131. · Zbl 1167.91354
[10] Vickrey, W.; Counterspeculation, auctions, and competitive sealed tenders; J. Financ.: 1961; Volume 16 ,8-37.
[11] Clarke, E.H.; Multipart pricing of public goods; Public Choice: 1971; Volume 11 ,17-33.
[12] Groves, T.; Incentives in teams; Econom. J. Econom. Soc.: 1973; Volume 41 ,617-631. · Zbl 0311.90002
[13] Kelly, F.P.; Maulloo, A.K.; Tan, D.K.; Rate control for communication networks: Shadow prices, proportional fairness and stability; J. Oper. Res. Soc.: 1998; Volume 49 ,237-252. · Zbl 1111.90313
[14] Yang, S.; Hajek, B.; Revenue and stability of a mechanism for efficient allocation of a divisible good; Preprint: 2005; .
[15] Maheswaran, R.; Başar, T.; Efficient signal proportional allocation (ESPA) mechanisms: Decentralized social welfare maximization for divisible resources; IEEE J. Sel. Areas Commun.: 2006; Volume 24 ,1000-1009.
[16] Sinha, A.; Anastasopoulos, A.; Mechanism design for resource allocation in networks with intergroup competition and intragroup sharing; IEEE Trans. Control Netw. Syst.: 2018; Volume 5 ,1098-1109. · Zbl 1515.91048
[17] Rabbat, M.; Nowak, R.; Distributed optimization in sensor networks; Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks: ; ,20-27.
[18] Boyd, S.; Parikh, N.; Chu, E.; ; Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers: Hanover, MA, USA 2011; . · Zbl 1229.90122
[19] Wei, E.; Ozdaglar, A.; Jadbabaie, A.; A distributed Newton method for network utility maximization-I: Algorithm; IEEE Trans. Autom. Control: 2013; Volume 58 ,2162-2175. · Zbl 1369.90194
[20] Alvarado, A.; Scutari, G.; Pang, J.S.; A new decomposition method for multiuser DC-programming and its applications; IEEE Trans. Signal Process.: 2014; Volume 62 ,2984-2998. · Zbl 1393.90091
[21] Di Lorenzo, P.; Scutari, G.; Distributed nonconvex optimization over time-varying networks; Proceedings of the 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP): ; ,4124-4128.
[22] Sinha, A.; Anastasopoulos, A.; Distributed mechanism design with learning guarantees for private and public goods problems; IEEE Trans. Autom. Control: 2020; Volume 65 ,4106-4121. · Zbl 1533.91115
[23] Heydaribeni, N.; Anastasopoulos, A.; Distributed Mechanism Design for Network Resource Allocation Problems; IEEE Trans. Netw. Sci. Eng.: 2020; Volume 7 ,621-636.
[24] Brown, G.W.; Iterative solution of games by fictitious play; Act. Anal. Prod. Alloc.: 1951; Volume 13 ,374-376. · Zbl 0045.09902
[25] Monderer, D.; Shapley, L.S.; Fictitious play property for games with identical interests; J. Econ. Theory: 1996; Volume 68 ,258-265. · Zbl 0849.90130
[26] Hofbauer, J.; Sandholm, W.H.; On the global convergence of stochastic fictitious play; Econometrica: 2002; Volume 70 ,2265-2294. · Zbl 1141.91336
[27] Milgrom, P.; Roberts, J.; Rationalizability, learning, and equilibrium in games with strategic complementarities; Econom. J. Econom. Soc.: 1990; Volume 58 ,1255-1277. · Zbl 0728.90098
[28] Scutari, G.; Palomar, D.P.; Facchinei, F.; Pang, J.S.; Monotone games for cognitive radio systems; Distributed Decision Making and Control: Berlin/Heidelberg, Germany 2012; ,83-112. · Zbl 1315.91005
[29] Polyak, B.; ; Introduction to Optimization: New York, NY, USA 1987; . · Zbl 0625.62093
[30] Srikant, R.; Ying, L.; ; Communication Networks: An Optimization, Control, and Stochastic Networks Perspective: Cambridge, UK 2013; . · Zbl 1350.90001
[31] Huang, Z.; Mitra, S.; Vaidya, N.; Differentially private distributed optimization; Proceedings of the 2015 International Conference on Distributed Computing and Networking: ; ,1-10.
[32] Cortés, J.; Dullerud, G.E.; Han, S.; Le Ny, J.; Mitra, S.; Pappas, G.J.; Differential privacy in control and network systems; Proceedings of the 2016 IEEE 55th Conference on Decision and Control (CDC): ; ,4252-4272.
[33] Nozari, E.; Tallapragada, P.; Cortés, J.; Differentially private distributed convex optimization via objective perturbation; Proceedings of the American Control Conference (ACC): ; ,2061-2066. · Zbl 1507.90131
[34] Han, S.; Topcu, U.; Pappas, G.J.; Differentially private distributed constrained optimization; IEEE Trans. Autom. Control: 2017; Volume 62 ,50-64. · Zbl 1359.90167
[35] Groves, T.; Ledyard, J.; Optimal allocation of public goods: A solution to the “free rider” problem; Econom. J. Econom. Soc.: 1977; Volume 45 ,783-809. · Zbl 0363.90015
[36] Hurwicz, L.; Outcome functions yielding Walrasian and Lindahl allocations at Nash equilibrium points; Rev. Econ. Stud.: 1979; Volume 46 ,217-225. · Zbl 0417.90027
[37] Huang, J.; Berry, R.A.; Honig, M.L.; Auction-based spectrum sharing; Mob. Netw. Appl.: 2006; Volume 11 ,405-418.
[38] Wang, B.; Wu, Y.; Ji, Z.; Liu, K.R.; Clancy, T.C.; Game theoretical mechanism design methods; IEEE Signal Process. Mag.: 2008; Volume 25 ,74-84.
[39] Wang, S.; Xu, P.; Xu, X.; Tang, S.; Li, X.; Liu, X.; TODA: Truthful online double auction for spectrum allocation in wireless networks; Proceedings of the 2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN): ; ,1-10.
[40] Ghosh, A.; Roth, A.; Selling privacy at auction; Proceedings of the 12th ACM Conference on Electronic Commerce: ; ,199-208. · Zbl 1318.91093
[41] Khalili, M.M.; Naghizadeh, P.; Liu, M.; Designing cyber insurance policies: Mitigating moral hazard through security pre-screening; Proceedings of the International Conference on Game Theory for Networks: Berlin/Heidelberg, Germany 2017; ,63-73. · Zbl 1375.91105
[42] Pal, R.; Wang, Y.; Li, J.; Liu, M.; Crowcroft, J.; Li, Y.; Tarkoma, S.; Data Trading with Competitive Social Platforms: Outcomes are Mostly Privacy Welfare Damaging; IEEE Trans. Netw. Serv. Manag.: 2020; .
[43] Caron, S.; Kesidis, G.; Incentive-based energy consumption scheduling algorithms for the smart grid; Proceedings of the 2010 First IEEE International Conference on Smart Grid Communications: ; ,391-396.
[44] Samadi, P.; Mohsenian-Rad, H.; Schober, R.; Wong, V.W.; Advanced demand side management for the future smart grid using mechanism design; IEEE Trans. Smart Grid: 2012; Volume 3 ,1170-1180.
[45] Muthirayan, D.; Kalathil, D.; Poolla, K.; Varaiya, P.; Mechanism design for demand response programs; IEEE Trans. Smart Grid: 2019; Volume 11 ,61-73.
[46] Iosifidis, G.; Gao, L.; Huang, J.; Tassiulas, L.; An iterative double auction for mobile data offloading; Proceedings of the 2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt): ; ,154-161.
[47] Johari, R.; Tsitsiklis, J.N.; Efficiency loss in a network resource allocation game; Math. Oper. Res.: 2004; Volume 29 ,407-435. · Zbl 1082.90015
[48] Yang, S.; Hajek, B.; VCG-Kelly mechanisms for allocation of divisible goods: Adapting VCG mechanisms to one-dimensional signals; IEEE J. Sel. Areas Commun.: 2007; Volume 25 ,1237-1243.
[49] Johari, R.; Tsitsiklis, J.N.; Efficiency of scalar-parameterized mechanisms; Oper. Res.: 2009; Volume 57 ,823-839. · Zbl 1233.91161
[50] Farhadi, F.; Golestani, S.J.; Teneketzis, D.; A surrogate optimization-based mechanism for resource allocation and routing in networks with strategic agents; IEEE Trans. Autom. Control: 2018; Volume 64 ,464-479. · Zbl 1482.90054
[51] Kakhbod, A.; Teneketzis, D.; An Efficient Game Form for Unicast Service Provisioning; IEEE Trans. Autom. Control: 2012; Volume 57 ,392-404. · Zbl 1370.68038
[52] Kakhbod, A.; Teneketzis, D.; Correction to “An Efficient Game Form for Unicast Service Provisioning” [Feb 12 392-404]; IEEE Trans. Autom. Control: 2015; Volume 60 ,584-585. · Zbl 1369.91032
[53] Sinha, A.; Anastasopoulos, A.; A General Mechanism Design Methodology for Social Utility Maximization with Linear Constraints; ACM Sigmetrics Perform. Eval. Rev.: 2014; Volume 42 ,12-15.
[54] Baumann, L.; Self-Ratings and Peer Review; 2018; .
[55] Bloch, F.; Olckers, M.; Friend-Based Ranking in Practice; ; .
[56] Chen, Y.; A family of supermodular NAvailable online: Ash mechanisms implementing Lindahl allocations; Econ. Theory: 2002; Volume 19 ,773-790. · Zbl 1011.91006
[57] Healy, P.J.; Mathevet, L.; Designing stable mechanisms for economic environments; Theor. Econ.: 2012; Volume 7 ,609-661. · Zbl 1395.91299
[58] Scutari, G.; Facchinei, F.; Pang, J.S.; Palomar, D.P.; Real and complex monotone communication games; IEEE Trans. Inf. Theory: 2014; Volume 60 ,4197-4231. · Zbl 1360.91101
[59] Gharesifard, B.; Cortés, J.; Distributed convergence to Nash equilibria in two-network zero-sum games; Automatica: 2013; Volume 49 ,1683-1692. · Zbl 1360.91012
[60] Ye, M.; Hu, G.; Game design and analysis for price-based demand response: An aggregate game approach; IEEE Trans. Cybern.: 2016; Volume 47 ,720-730.
[61] Grammatico, S.; Dynamic control of agents playing aggregative games with coupling constraints; IEEE Trans. Autom. Control: 2017; Volume 62 ,4537-4548. · Zbl 1390.91063
[62] Yi, P.; Pavel, L.; Distributed generalized Nash equilibria computation of monotone games via double-layer preconditioned proximal-point algorithms; IEEE Trans. Control Netw. Syst.: 2018; Volume 6 ,299-311. · Zbl 1515.91023
[63] Paccagnan, D.; Gentile, B.; Parise, F.; Kamgarpour, M.; Lygeros, J.; Nash and Wardrop equilibria in aggregative games with coupling constraints; IEEE Trans. Autom. Control: 2018; Volume 64 ,1373-1388. · Zbl 1482.91045
[64] Parise, F.; Ozdaglar, A.; A variational inequality framework for network games: Existence, uniqueness, convergence and sensitivity analysis; Games Econ. Behav.: 2019; Volume 114 ,47-82. · Zbl 1419.91160
[65] Xiao, Y.; Hou, X.; Hu, J.; Distributed solutions of convex-concave games on networks; Proceedings of the 2019 American Control Conference (ACC): ; ,1189-1194.
[66] Bimpikis, K.; Ehsani, S.; Ilkılıç, R.; Cournot competition in networked markets; Manag. Sci.: 2019; Volume 65 ,2467-2481.
[67] Zhang, K.; Yang, Z.; Başar, T.; Policy optimization provably converges to Nash equilibria in zero-sum linear quadratic games; arXiv: 2019; .
[68] uz Zaman, M.A.; Zhang, K.; Miehling, E.; Bașar, T.; Reinforcement learning in non-stationary discrete-time linear-quadratic mean-field games; Proceedings of the 2020 59th IEEE Conference on Decision and Control (CDC): ; ,2278-2284.
[69] Roudneshin, M.; Arabneydi, J.; Aghdam, A.G.; Reinforcement learning in nonzero-sum Linear Quadratic deep structured games: Global convergence of policy optimization; Proceedings of the 2020 59th IEEE Conference on Decision and Control (CDC): ; ,512-517.
[70] Shi, Y.; Zhang, B.; Multi-agent reinforcement learning in Cournot games; Proceedings of the 2020 59th IEEE Conference on Decision and Control (CDC): ; ,3561-3566.
[71] Sohet, B.; Hayel, Y.; Beaude, O.; Jeandin, A.; Learning Pure Nash Equilibrium in Smart Charging Games; Proceedings of the 2020 59th IEEE Conference on Decision and Control (CDC): ; ,3549-3554.
[72] Sinha, A.; Mechanism Design with Allocative, Informational and Learning Constraints; Ph.D. Thesis: 2017; .
[73] Zhou, X.; On the Fenchel duality between strong convexity and Lipschitz continuous gradient; arXiv: 2018; .
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