• Journal of KIISE:Software and Applications
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• v.27 no.3
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• pp.257-265
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• 2000

There is much selective confliction in nature where selfish and rational individuals exists. Iterated Prisoner's Dilemma (IPD) game deals with this problem, and has been used to study on the evolution of cooperation in social, economic and biological systems. So far, there has been much work about the relationship of the number of players and cooperation, strategy learning as a machine learning and the effect of payoff functions to cooperation. In this paper, We attempt to investigate the cooperative coalition size according to payoff functions, and observe the relationship of localization and the evolution of cooperation in NIPD (N-player IPD) game. Experimental results indicate that cooperative coalition size increases as the gradient of the payoff function for cooperation becomes steeper than that of defector's payoff function, or as the minimum coalition size gets smaller, Moreover, the smaller the neighborhood of interaction is, the higher the cooperative coalition emerges through the evolution of population.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.712-717
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• 2011

Option issuers generally utilize Dynamic Delta Hedging(DDH) technique to avoid the risk resulting from continuously changing option value. DDH duplicates payoff of option position by adjusting hedge position according to the delta value from Black-Scholes(BS) model in order to maintain risk neutral state. DDH, however, is not able to guarantee optimal hedging performance because of the weaknesses caused by impractical assumptions inherent in BS model. Therefore, this study presents a methodology for dynamic option hedge using artificial neural network(ANN) to enhance hedging performance and show the superiority of the proposed method using various computational experiments.

• Journal of Technology Innovation
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• v.15 no.1
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• pp.175-201
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• 2007

Licensing contracts between partners in International Joint Ventures(IJV) have not only aspects of relation contract, which is interdependent and long-term cooperative relationships in interpartner but also aspects of discrete contract which is exposed to opportunistic risk caused by IJV partners who maximize individual profit instead of joint payoff maximization. In this circumstance, appropriate compensation structures such as lump-sum and royalty can reduce conflicts and spur interpartner cooperation. In addition, compensation structures that stipulate each party's rights, duties, and responsibilities under various sets of environmental conditions have strong implications for transaction cost minimization and joint payoff maximization. On the other hands, compensation structures such as lump-sum and royalty in IJV licensing contract have benefits and costs depending on IJV partners uncertainty, partner dependency, and environment uncertainty. Therefore, the purpose of this paper is to empirically show how partner uncertainty, partner dependence and environment uncertainty influence compensation structure chosen by licensor in IJV.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.6
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• pp.347-353
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• 2003

In models of imperfect competition of deregulated electricity markets, the key task is to find the Nash equilibrium(NE). The approaches for finding the NE have had two major bottlenecks: computation of mixed strategy equilibrium and treatment of multi-player games. This paper proposes a payoff matrix approach that resolves these bottlenecks. The proposed method can efficiently find a mixed strategy equilibrium in a multi-player game. The formulation of the m condition for a three-player game is introduced and a basic computation scheme of solving nonlinear equalities and checking inequalities is proposed. In order to relieve the inevitable burden of searching the subspace of payoffs, several techniques are adopted in this paper. Two example application problems arising from electricity markets and involving a Cournot and a Bertrand model, respectively, are investigated for verifying the proposed method.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.214-225
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• 2001

This research deals with an off-line learning method targeted for systematically constructing negotiation strategies in automated electronic commerce. Single-issue negotiation is assumed. Variants of competitive learning and hierarchical clustering method are devised and applied to extracting negotiation strategies, given historical negotiation data set and tactics. Our research is motivated by the following fact: evidence from both theoretical analysis and observations of human interaction shows that if decision makers have prior knowledge on the behaviors of opponents from negotiation, the overall payoff would increase. Simulation-based experiments convinced us that the proposed method is more effective than human negotiation in terms of the ratio of negotiation settlement and resulting payoff.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.320-329
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• 2010

As software producers have tried to keep their profit against illegal piracy, contents producers also want to protect their contents from unlawful sharing among users. Some researchers uncovered that the regulation on the unlicensed contents is not the best policy to maximize their profit mainly due to network effect but this issue has been still controversial. In this paper, we develop a model to investigate the effect of regulation against unlicensed contents sharing on the profit of contents producers and present the optimal condition to maximize profit of contents producers under the regulation and non-regulation of unlicensed contents. As a result, we analyzed that the firm's payoff under the regulation on unlicensed contents is not always greater than the payoff under the non-regulation because of network externality. If the additional utility from off-line purchase of type P consumers (who enjoy the additional benefit of off-line purchase) is large enough, then the firm's payoff is maximized without regulation.

• Journal of Information Technology Applications and Management
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• v.14 no.1
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• pp.21-36
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• 2007

We face with numerous situation of decision making. In this situation, we would make decision through individual's own information, or others' decision making with ignoring private information, Also we would make decision through compromise of private information and others' information. like this, we call situation to imitate information of previous decision maker, with disregarding private own information,'information cascades' Also, anchoring effects are results of insufficient adjustment from an arbitrary value. In this paper, we examined how information cascades effects and anchoring effects would be generated in the people who use IT technique as instant poll of website. And this paper presents alternatives to decrease information cascades effects and anchoring effects. This exercise provides facts anchoring effects occur when voters can see poll result. And this paper shows that more degree of output difference is deepened, and more anchoring effects occur. Also this paper shows that when website gives positive payoff, more anchoring effects occur.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.11
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• pp.630-635
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• 2004

Generation companies(Genco) submit the supply functions as a bidding function to a bid market in a competitive electricity market. The profits of Gencos vary in accordance with the bid functions, so the selection of a bidding function plays a key role in increasing their profits. In order to get a profitable bidding function which is usually linear, it is required to modify adequately the intersection and the slope of a linear supply function. This paper presents an analysis of the selection of the supply function from the viewpoint of Nash equilibrium(NE). Four types of bidding function parameters are used for analizing the electricity market. The competition of selecting bidding parameters is modeled as two level games in this research. One is a subgame where a certain type of parameters is given and the players compete to select values of the underlying parameters. The other is an overall game where the players compete to select a profitable type among the four types of parameters. The NEs in both games are computed by an using analytic method and a payoff matrix method. It is verified in case studies for the NE of overall game to satisfy the equilibrium condition.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.2
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• pp.89-98
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• 2007

In this paper the economic value of weather forecasts is valuated for profit-oriented enterprise decision-making situations. Value is estimated in terms of monetary profits (or benefits) resulted from the forecast user's decision under the specific payoff structure, which is represented by a profit/loss ratio model combined with a decision function and a value score (VS). The forecast user determines a business-related decision based on the probabilistic forecast, the user's subjective reliability of the forecasts, and the payoff structure specific to the user's business environment. The VS curve for a meteorological forecast is specified by a function of the various profit/loss ratios, providing the scaled economic value relative to the value of a perfect forecast. The proposed valuation method based on the profit/loss ratio model and the VS is adapted for hypothetical sets of forecasts and verified for site-specific probability of precipitation forecast of 12 hour and 24 hour-lead time, which is generated from Korea meteorological administration (KMA). The application results show that forecast information with shorter lead time can provide the decision-makers with great benefits and there are ranges of profit/loss ratios in which high subjective reliability of the given forecast is preferred.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1554-1566
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• 2014

Cloud Computing allows application providers seamlessly scaling their services and enables users scaling their usage according to their needs. In this paper, using queuing game model, we present service scheduling schemes which are used in software as a service (SaaS). The object is maximizing the Cloud Computing platform's (CCP's) payoff via controlling the service requests whether to join or balk, and controlling the value of CCP's admission fee. Firstly, we treat the CCP as one virtual machine (VM) and analyze the optimal queue length with a fixed admission fee distribution. If the position number of a new service request is bigger than the optimal queue length, it balks. Otherwise, it joins in. Under this scheme, the CCP's payoff can be maximized. Secondly, we extend this achievement to the multiple VMs situation. A big difference between single VM and multiple VMs is that the latter one needs to decide which VM the service requests turn to for service. We use a corresponding algorithm solve it. Simulation results demonstrate the good performance of our schemes.