This paper addresses a multi-agent scheduling problem with uniform parallel machines owned by a resource agent and competing jobs with dynamic arrival times that belong to different consumer agents.All agents are self...This paper addresses a multi-agent scheduling problem with uniform parallel machines owned by a resource agent and competing jobs with dynamic arrival times that belong to different consumer agents.All agents are self-interested and rational with the aim of maximizing their own objectives,resulting in intense resource competition among consumer agents and strategic behaviors of unwillingness to disclose private information.Within the context,a centralized scheduling approach is unfeasible,and a decentralized approach is considered to deal with the targeted problem.This study aims to generate a stable and collaborative solution with high social welfare while simultaneously accommodating consumer agents’preferences under incomplete information.For this purpose,a dynamic iterative auction-based approach based on a decentralized decision-making procedure is developed.In the proposed approach,a dynamic auction procedure is established for dynamic jobs participating in a realtime auction,and a straightforward and easy-to-implement bidding strategy without price is presented to reduce the complexity of bid determination.In addition,an adaptive Hungarian algorithm is applied to solve the winner determination problem efficiently.A theoretical analysis is conducted to prove that the proposed approach is individually rational and that the myopic bidding strategy is a weakly dominant strategy for consumer agents submitting bids.Extensive computational experiments demonstrate that the developed approach achieves high-quality solutions and exhibits considerable stability on largescale problems with numerous consumer agents and jobs.A further multi-agent scheduling problem considering multiple resource agents will be studied in future work.展开更多
In many auctions,buyers know beforehand little about objects to be sold in the future.Whether and how to reveal information about future objects is an important decision problem for sellers.In this paper,two objects a...In many auctions,buyers know beforehand little about objects to be sold in the future.Whether and how to reveal information about future objects is an important decision problem for sellers.In this paper,two objects are sold sequentially and each buyer's valuation for the second object is k times that for the first one,and the true value of k is sellers' private information.The authors identify three factors which affect sellers' revelation strategies: The market's competition intensity which is characterized by the number of buyers,buyers' prior information about the second object,and the difference degree between two objects which is characterized by k.The authors give not only conditions under which revealing information about the second object in advance benefits the seller,but also the optimal releasing amount of information in the market with two sellers and one seller,respectively.展开更多
In sequential auctions the phenomenon of declining prices is often observed, which in theory can be represented by a supermartingale. This paper employs the perspective that bidders' values may change over stages ...In sequential auctions the phenomenon of declining prices is often observed, which in theory can be represented by a supermartingale. This paper employs the perspective that bidders' values may change over stages and the common priors are sequentially adjusted by the remaining bidders. It is shown that the declining price sequence can be explained by the adjustment of common priors between auctions. The adjustment of common priors is characterized by stochastic orders. Sufficient and necessary conditions for a supermartingale price sequence are derived.展开更多
In this paper we reanalyze Said’s(2011) work by retaining all his assumptions except that we use the first-price auction to sell differentiated goods to buyers in dynamic markets instead of the second-price auction. ...In this paper we reanalyze Said’s(2011) work by retaining all his assumptions except that we use the first-price auction to sell differentiated goods to buyers in dynamic markets instead of the second-price auction. We conclude that except for the expression of the equilibrium bidding strategy, all the results for the first-price auction are exactly the same as the corresponding ones for the second-price auction established by Said(2011). This implies that the well-known "revenue equivalence theorem"holds true for Said’s(2011) dynamic model setting.展开更多
大多数序贯拍卖模型中的标的只具有一个属性,本文构造了一个标的兼有共同价值和私人价值两个属性的序贯拍卖模型。考虑在拍卖过程中公开标的信息,分别给出此模型下买家Agent在第一价格密封拍卖规则(The First Price Sealed Auction,FPSA...大多数序贯拍卖模型中的标的只具有一个属性,本文构造了一个标的兼有共同价值和私人价值两个属性的序贯拍卖模型。考虑在拍卖过程中公开标的信息,分别给出此模型下买家Agent在第一价格密封拍卖规则(The First Price Sealed Auction,FPSA)和第二价格密封拍卖规则(The Second Price Sealed Auction,SPSA)中的竞价策略函数。提出一个基于标的信息增益比率的分类算法LIWNB,使得买家Agent在提交竞价时能准确分类当前拍卖信息,精确估计标的的共同价值。实验结果显示,算法LIWNB在一定条件下具有较高的分类性能。展开更多
The task assignment of multi-agent system has attracted considerable attention;however,the contradiction between computational complexity and assigning performance remains to be resolved.In this paper,a novel consensu...The task assignment of multi-agent system has attracted considerable attention;however,the contradiction between computational complexity and assigning performance remains to be resolved.In this paper,a novel consensus-based adaptive optimization auction(CAOA)algorithm is proposed to greatly reduce the computation load while attaining enhanced system payoff.A new optimization scheme is designed to optimize the critical control parameter in the price update role of auction algorithm which can reduce the searching complexity in obtaining a better bidding price.With this new scheme,the CAOA algorithm is designed.Then the developed algorithm is applied to the multi-AUV task assignment problem for underwater detection mission in complex environments.The simulation and comparison studies verify the effectiveness and advantage of the CAOA algorithm.展开更多
基金supported by the National Natural Science Foundation of China(51975482)the China Scholarship Council.
文摘This paper addresses a multi-agent scheduling problem with uniform parallel machines owned by a resource agent and competing jobs with dynamic arrival times that belong to different consumer agents.All agents are self-interested and rational with the aim of maximizing their own objectives,resulting in intense resource competition among consumer agents and strategic behaviors of unwillingness to disclose private information.Within the context,a centralized scheduling approach is unfeasible,and a decentralized approach is considered to deal with the targeted problem.This study aims to generate a stable and collaborative solution with high social welfare while simultaneously accommodating consumer agents’preferences under incomplete information.For this purpose,a dynamic iterative auction-based approach based on a decentralized decision-making procedure is developed.In the proposed approach,a dynamic auction procedure is established for dynamic jobs participating in a realtime auction,and a straightforward and easy-to-implement bidding strategy without price is presented to reduce the complexity of bid determination.In addition,an adaptive Hungarian algorithm is applied to solve the winner determination problem efficiently.A theoretical analysis is conducted to prove that the proposed approach is individually rational and that the myopic bidding strategy is a weakly dominant strategy for consumer agents submitting bids.Extensive computational experiments demonstrate that the developed approach achieves high-quality solutions and exhibits considerable stability on largescale problems with numerous consumer agents and jobs.A further multi-agent scheduling problem considering multiple resource agents will be studied in future work.
基金supported by the National Natural Science Foundation of China under Grant Nos.61273206 and 71471069
文摘In many auctions,buyers know beforehand little about objects to be sold in the future.Whether and how to reveal information about future objects is an important decision problem for sellers.In this paper,two objects are sold sequentially and each buyer's valuation for the second object is k times that for the first one,and the true value of k is sellers' private information.The authors identify three factors which affect sellers' revelation strategies: The market's competition intensity which is characterized by the number of buyers,buyers' prior information about the second object,and the difference degree between two objects which is characterized by k.The authors give not only conditions under which revealing information about the second object in advance benefits the seller,but also the optimal releasing amount of information in the market with two sellers and one seller,respectively.
基金supported by Beijing Higher Education Young Elite Teacher Project(YETP0964)the National Natural Science Foundation of China under Grant Nos.71171053 and 71473282+1 种基金211 Projects FoundationProjects from School of Economics at Central University of Finance and Economics
文摘In sequential auctions the phenomenon of declining prices is often observed, which in theory can be represented by a supermartingale. This paper employs the perspective that bidders' values may change over stages and the common priors are sequentially adjusted by the remaining bidders. It is shown that the declining price sequence can be explained by the adjustment of common priors between auctions. The adjustment of common priors is characterized by stochastic orders. Sufficient and necessary conditions for a supermartingale price sequence are derived.
基金Supported by the National Natural Science Foundation of China(71171052)
文摘In this paper we reanalyze Said’s(2011) work by retaining all his assumptions except that we use the first-price auction to sell differentiated goods to buyers in dynamic markets instead of the second-price auction. We conclude that except for the expression of the equilibrium bidding strategy, all the results for the first-price auction are exactly the same as the corresponding ones for the second-price auction established by Said(2011). This implies that the well-known "revenue equivalence theorem"holds true for Said’s(2011) dynamic model setting.
文摘大多数序贯拍卖模型中的标的只具有一个属性,本文构造了一个标的兼有共同价值和私人价值两个属性的序贯拍卖模型。考虑在拍卖过程中公开标的信息,分别给出此模型下买家Agent在第一价格密封拍卖规则(The First Price Sealed Auction,FPSA)和第二价格密封拍卖规则(The Second Price Sealed Auction,SPSA)中的竞价策略函数。提出一个基于标的信息增益比率的分类算法LIWNB,使得买家Agent在提交竞价时能准确分类当前拍卖信息,精确估计标的的共同价值。实验结果显示,算法LIWNB在一定条件下具有较高的分类性能。
基金supported by the National Natural Science Foundation of China(Grant Nos.62273281,U22B2039,and 61922068)。
文摘The task assignment of multi-agent system has attracted considerable attention;however,the contradiction between computational complexity and assigning performance remains to be resolved.In this paper,a novel consensus-based adaptive optimization auction(CAOA)algorithm is proposed to greatly reduce the computation load while attaining enhanced system payoff.A new optimization scheme is designed to optimize the critical control parameter in the price update role of auction algorithm which can reduce the searching complexity in obtaining a better bidding price.With this new scheme,the CAOA algorithm is designed.Then the developed algorithm is applied to the multi-AUV task assignment problem for underwater detection mission in complex environments.The simulation and comparison studies verify the effectiveness and advantage of the CAOA algorithm.
