• Asian Journal of Business Environment
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• v.10 no.2
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• pp.5-15
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• 2020

Purpose: This study examines the impact of individual reciprocal preferences on coalition formation. The reciprocal model considers a player's own payoff, the player's perception of others' payoffs, and others' perceptions of the player's payoff. Research design, data and methodology: A reciprocal model is built to illustrate how reciprocity influences individual decisions in a coalition game and its formation. The prediction is examined with experimental evidences from a dictator game and a membership game. Results: The theoretical result suggests that the coalition formation could be unstable due to negative reciprocal kindness. The experimental findings support that negative reciprocal kindness could lead players participating in a coalition, no matter their dominant strategies are. When subjects were essential to make contributions to a coalition, they were more likely to cooperate if they were treated badly. In contrast, when subjects were unnecessary, the reciprocal kindness could enhance cooperative tendencies. Conclusions: This study reveals that the reciprocal behavior could influence individual decisions and reshape the coalition formation. In terms of policy implications, this study has shown that coalition formation could be reshaped by reciprocal prefe rences. Due to the strategic and complicated decision process in an interactive environment, a comprehensive investigation of factors would be required in a climate coalition in practice.

• The KIPS Transactions:PartC
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• v.17C no.4
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• pp.385-390
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• 2010

Fair and efficient bandwidth allocation methods using the coalition game theory and the bargaining game theory following the axiomatic approach have been proposed when sending nodes with different traffic input rate try to share the bandwidth. These methods satisfy the axiomatic fairness provided by the mathematical ground of the game theories. However, since the axioms of the two game models are different from one another, the allocated bandwidths to each sending nodes become different even in the same communication environments. Thus, in this paper, we model the bandwidth allocation problem with these game theories, and quantitatively compare and analyze the allocated bandwidth and loss rate of each sending nodes in various communication environments. The results show that the bargaining game allocates relatively less bandwidth to a node with a higher sending rate than that with a lower sending rate while coalition game allocates bandwidth according to the sending rate of each node.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4220-4241
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• 2017

For the downlink energy-harvesting small cell network, this paper proposes an interference management algorithm based on distributed coalitional game. The cooperative interference management problem of the energy-harvesting small cells is modeled as a coalitional game with transfer utility. Based on the energy harvesting strategy of the small cells, the time sharing mode of the small cells in the same coalition is determined, and an optimization model is constructed to maximize the total system rate of the energy-harvesting small cells. Using the distributed algorithm for coalition formation proposed in this paper, the stable coalition structure, optimal time sharing strategy and optimal power distribution are found to maximize the total utility of the small cell system. The performance of the proposed algorithm is discussed and analyzed finally, and it is proved that this algorithm can converge to a stable coalition structure with reasonable complexity. The simulations show that the total system rate of the proposed algorithm is superior to that of the non-cooperative algorithm in the case of dense deployment of small cells, and the proposed algorithm can converge quickly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3312-3334
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• 2015

In this paper, a mechanism for spectrum allocation in overlay cognitive radio networks is proposed. In overlay cognitive radio networks, the secondary users (SUs) must first sense the activity of primary users (PUs) to identify unoccupied spectrum bands. Based on their different contributions for the spectrum sensing, the SUs get payoffs that are computed by the fusion center (FC). The unoccupied bands will be auctioned and SUs are asked to bid using payoffs they earned or saved. Coalitions are allowed to form among SUs because each SU may only need a portion of the bands. We formulate the coalition forming process as a coalition forming game and analyze it by game theory. In the coalition formation game, debtor-creditor relationship may occur among the SUs because of their limited payoff storage. A debtor asks a creditor for payoff help, and in return provides the creditor with a portion of transmission time to relay data for the creditor. The negotiations between debtors and creditors can be modeled as a Bayesian game because they lack complete information of each other, and the equilibria of the game is investigated. Theoretical analysis and numerical results show that the proposed auction yields data rate improvement and certain fairness among all SUs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3413-3430
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• 2017

With the fast increasing popularity of mobile services, ubiquitous mobile devices with enhanced sensing capabilities collect and share local information towards a common goal. The recent Mobile Crowd Sensing (MCS) paradigm enables a broad range of mobile applications and undoubtedly revolutionizes many sectors of our life. A critical challenge for the MCS paradigm is to induce mobile devices to be workers providing sensing services. In this study, we examine the problem of sensing task assignment to maximize the overall performance in MCS system while ensuring reciprocal advantages among mobile devices. Based on the overlapping coalition game model, we propose a novel workload determination scheme for each individual device. The proposed scheme can effectively decompose the complex optimization problem and obtains an effective solution using the interactive learning process. Finally, we have conducted extensive simulations, and the results demonstrate that the proposed scheme achieves a fair tradeoff solution between the MCS performance and the profit of individual devices.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1415-1423
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• 2016

Interference in device-to-device (D2D) communication underlaying cellular network needs to be elaborately investigated because of channel sharing. The objective is to improve the quality of D2D communications while maintaining high performance for cellular users. In this paper, we solve the above problem by jointly considering channel allocation and power control using coalition formation game. Our cooperative game theoric approach allows to enhance network-wide performance. We design a merge-and-split algorithm to deal with the complexity of the combinatorial structure in coalition formation problem. The analytical and numerical results show that our algorithm converges to a stable point which achieves high network performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.611-627
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• 2017

For enhancing the coverage of wireless networks and increasing the spectrum efficiency, small cell networks (SCNs) are considered to be one of the most prospective schemes. Most of the existing literature on resource allocation among non-cooperative small cell base stations (SBSs) has widely drawn close attention and there are only a small number of the cooperative ideas in SCNs. Based on the motivation, we further investigate the cooperative approach, which is formulated as a coalition formation game with power control algorithm (CFG-PC). First, we formulate the downlink sub-channel resource allocation problem in an SCN as a coalition formation game. Pareto order and utilitarian order are applied to form coalitions respectively. Second, to achieve more availability and efficiency power assignment, we expand and solve the power control using particle swarm optimization (PSO). Finally, with our proposed algorithm, each SBS can cooperatively work and eventually converge to a stable SBS partition. As far as the transmit rate of per SBS and the system rate are concerned respectively, simulation results indicate that our proposed CFG-PC has a significant advantage, relative to a classical coalition formation algorithm and the non-cooperative case.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.101-110
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• 2004

In dynamic systems, such as social and economic systems, complex interactions emerge among its members. In that case, their behaviors become adaptive according to Changing environment. In many cases, an individual's behaviors can be modeled by a stimulus-response system in a dynamic environment. In this paper, we use the Iterated Prisoner's Dilemma (IPD) game, which is simple yet capable of dealing with complex problems, to model the dynamic systems. We propose strategic coalition consisting of many agents and simulate their emergence in a co-evolutionary learning environment. Also we introduce the concept of confidence for agents in a coalition and show how such confidences help to improve the generalization ability of the whole coalition. Experimental results are presented to demonstrate that co-evolutionary learning with coalitions and confidence allows better performing strategies that generalize well.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.1
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• pp.1-8
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• 2019

In this paper, we design a new mobile crowdsourcing control scheme based on the incentive mechanism. By using a novel incentive mechanism, mobile nodes can get the maximum payoff when they report their true private information. As mobile nodes participate in the overlapping coalition formation game, they can effectively invest their resource while getting the higher reward. Simulation results clearly indicate that the proposed scheme has a better performance than the other existing schemes under various mobile crowdsourcing environments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.220-227
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• 2018

The cooperative game theory consists of a set of players and utility function that has positive values for a subset of players, called coalition, in the game. The purpose of cost allocation method is to allocate the relevant cost among game players in a fair and rational way. Therefore, cost allocation method based on cooperative game theory has been applied in many areas for fair and reasonable cost allocation. On the other hand, the desirable characteristics of the cost allocation method are Pareto optimality, rationality, and marginality. Pareto optimality means that costs are entirely paid by participating players. Rationality means that by joining the grand coalition, players do not pay more than they would if they chose to be part of any smaller coalition of players. Marginality means that players are charged at least enough to cover their marginal costs. If these characteristics are all met, the solution of cost allocation method exists in the core. In this study, proportional method is applied to EOQ inventory game and EPQ inventory game with shortage. Proportional method is a method that allocates costs proportionally to a certain allocator. This method has been applied to a variety of problems because of its convenience and simple calculations. However, depending on what the allocator is used for, the proportional method has a weakness that its solution may not exist in the core. Three allocators such as demand, marginal cost, and cost are considered. We prove that the solution of the proportional method to demand and the proportional method to marginal cost for EOQ game and EPQ game with shortage is in the core. The counterexample also shows that the solution of the proportional method to cost does not exist in the core.