• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.292-300
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• 2020

According to the development of artificial intelligence technology, attempts have been made to interpret phenomena in various fields of the real world such as economic, social, and scientific fields through computer simulations using virtual artificial agents. In the existing artificial agent-based bargaining game analysis, there was a problem that did not reflect the cost incurred when the stage progresses in the real-world bargaining game and the depreciation of the bargaining target over time. This study intends to observe the effect on the bargaining game by adding the cost incurred in the bargaining stage and depreciation of the bargaining target over time (bargaining cost) to the previous artificial agent-based bargaining game model. As a result of the experiment, it was observed that as the cost incurred in the bargaining stage increased, the two artificial agents participating in the game had a share close to half the ratio and tried to conclude the negotiation in the early stage.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.37-45
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• 2005

This paper presents a relationship between Nash bargaining game and Wardrop user equilibrium, which has been widely used in transportation modeling for route choice problem. Wardrop user equilibrium assumes that drivers in road network have perfect information on the traffic conditions and they choose their optimal paths without cooperation each other. In this regards, if the bargaining game process is introduced in route choice modeling, we may avoid the strong assumptions to some extent. For such purpose, this paper derives a theorem that Nash bargaining solution is equivalent to Wardrop user equilibrium as the barging process continues and prove it with some numerical examples. The model is formulated based on two-person bargaining game. and n-person game is remained for next work.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.172-179
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• 2006

Over the past few years, a considerable number of studies have been conducted on modeling the bargaining game using artificial agents on within-model interaction. However, very few attempts have been made at study on between-model interaction. This paper investigates the interaction and co-evolutionary process among heterogeneous artificial agents in the bargaining game. We present two kinds of the artificial agents participating in the bargaining game. They play some bargaining games with their strategies based on genetic algorithm (GA) and reinforcement learning (RL). We compare agents' performance between two agents under various conditions which are the changes of the parameters of artificial agents and the maximal number of round in the bargaining game. Finally, we discuss which agents show better performance and why the results are produced.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.549-557
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• 2014

Recently, analysis of bargaining game using evolutionary computation is essential issues in field of game theory. In this paper, we observe a bargaining game using co-evolution between two heterogenous artificial agents. In oder to model two artificial agents, we use a particle swarm optimization and a differential evolution. We investigate algorithm parameters for the best performance and observe that which strategy is better in the bargaining game under the co-evolution between two heterogenous artificial agents. Experimental simulation results show that particle swarm optimization outperforms differential evolution in the bargaining game.

• Korea Trade Review
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• v.44 no.3
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• pp.105-121
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• 2019

This study applies diverse game theories to the US-China Trade War. The US-China Trade War can be analyzed as a game situation because the strategic decision-making process to maximize one's profit while considering the reaction of the other party is a game situation. However, related research suffered from some mistakes in applying the US-China Trade War as it is to classic game theory, because while the prisoners dilemma is based on the situation of No Communication, No Trust, No Cooperation, the US-China Trade War has a precondition different from that of prisoners dilemma, since it mutually communicates information and negotiation is repeated several times in a cooperative situation. The result of the trade negotiation will likely end as 'cooperate-cooperate'. Further, considering trade volume, trade interdependence, bargaining power based on economy, and the scale of damage caused by the Trade War, the US-China Trade War is progressing with the bargaining power of the US being higher than that of China. Since the current US-China Trade War is in an asymmetrical situation under the dominant bargaining power of the US, it is likely to reach 'US defect-China cooperative' in the long run.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.246-248
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• 2012

In this paper, we recommend some game theoretical schemes try to get reliability transmission and resource allocation of the contention free period in overlapped WBAN(Wireless Body Area Net works) environment. Cooperative bargaining game is considered to guarantee a reliability conflict-free transmission. We study it by considering the priorty of device and the demand number of allocated timeslots in the CFP (Contention Free Period), and guarantee the least requested timeslots through bargaining between each user.

• 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.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.293-303
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• 2016

Analysis of bargaining games utilizing evolutionary computation in recent years has dealt with important issues in the field of game theory. In this paper, we investigated interaction and coevolution process among heterogeneous artificial agents using evolutionary computation in the bargaining game. We present three kinds of evolving-strategic agents participating in the bargaining games; genetic algorithms (GA), particle swarm optimization (PSO) and differential evolution (DE). The co-evolutionary processes among three kinds of artificial agents which are GA-agent, PSO-agent, and DE-agent are tested to observe which EC-agent shows the best performance in the bargaining game. The simulation results show that a PSO-agent is better than a GA-agent and a DE-agent, and that a GA-agent is better than a DE-agent with respect to co-evolution in bargaining game. In order to understand why a PSO-agent is the best among three kinds of artificial agents in the bargaining game, we observed the strategies of artificial agents after completion of game. The results indicated that the PSO-agent evolves in direction of the strategy to gain as much as possible at the risk of gaining no property upon failure of the transaction, while the GA-agent and the DE-agent evolve in direction of the strategy to accomplish the transaction regardless of the quantity.

• ETRI Journal
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• v.33 no.6
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• pp.957-960
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• 2011

We present a fair and efficient solution for selfish readers with the Nash bargaining solution (NBS) to mitigate the effects of RFID frequency interference. We compare the NBS with a solution derived by the max log-sum scheme that maximizes total utility and show that for selfish and rational readers, the NBS brings success in bargaining on resource allocation between readers unlike the max log-sum scheme, although the NBS has less total payoff compared to the max log-sum scheme.

• The KIPS Transactions:PartC
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• v.18C no.2
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• pp.97-102
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• 2011

Since the game theory provides a theoretical ground to distribute a shared resource between demanding users in a fair and efficient manner, it has been used for the bandwidth allocation problem in a network. However, the bandwidth allocation schemes with different game theory assign different amount of bandwidth in the same operational environments. However, only the mathematical framework is adopted when a bandwidth allocation scheme is devised without quantitatively comparing the results when they applied to the bandwidth allocation problem. Thus, in this paper, we compare the characteristics of the bandwidth allocation schemes using the bankrupt game theory and the bargaining game theory when they applied to the situation where nodes are competing for the bandwidth in a network. Based on the numerical results, we suggest the future research direction.