• Journal of Gifted/Talented Education
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• v.27 no.1
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• pp.59-80
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• 2017

In this study, we investigate social preference of gifted students by analyzing their behaviors in social dilemma situations. We conducted an experimental study using ultimatum games and public goods games with 132 academically gifted middle school students who attended the Ewha-Seodaemun Center for gifted education from 2012 to 2016. We also experimented the same games with 87 regular students for comparative analysis. The result of ultimatum game experiment shows that there is no statistical difference in the proposed share of both groups. Their proposed share ranges from 37% to 38% as expected in other similar studies. However, the rejection rate of the respondents to the proposals with small share are significantly higher among gifted students than among their regular counterparts. This result implies that the gifted students show stronger negative reciprocity, meaning that they tend to punish selfish behaviors even when it takes some costs. In finitely repeated public goods game experiments, the results show that both groups' contribution rates decrease toward the end of the experiments. However, the gifted students show strategic cooperation by attempting to increase the other members' contribution rate within an experimental group. This implies that gifted students tend to care more about how to increase their own expected rewards by reciprocating other students' behaviors.

• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.85-97
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• 2005

At th first time in 1985, Tetris appeared, it became game that are loved to many users until now. Existent Tetris employed way to give score according to number of that is destroyed whenever line are destroyed, and give advantage about serial attack and so on, But, these score calculation method gave so fixed and simple pattern. In this paper, We design and implement the new tetris game System by score calculation method per level that Is different with existent method. That Is, this method is to compare present and before with number of destroyed line and give advantage in basis score, Also, It is going to permit strategic utilization of still more developed tetris than existent tetris using score calculation method per level.

• Journal of Korea Game Society
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• v.18 no.6
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• pp.59-68
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• 2018

In spite of its simple rule, Go is one of the most complex strategic board games in the field of Artificial Intelligence (AI). Monte-Carlo Tree Search (MCTS) is an algorithm with best-first tree search, and has used to implement computer Go. We try to find the most promising first move using MCTS for playing a Go game on a board of size smaller than $9{\times}9$ Go board. The experimental result reveals that MCTS prefers to place the first move at the center in case of odd-sized Go boards, and at the central in case of even-sized Go boards.

• Journal of Platform Technology
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• v.9 no.1
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• pp.3-14
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• 2021

Cognitive Radio network (CR) is a promising paradigm that helps the unlicensed user (Secondary User) to analyse the spectrum and coordinate the spectrum access to support the creation of common control channel (CCC). The cooperation of secondary users and broadcasting between them is done through transmitting messages in CCC. In case, if the control channels may get jammed and it may directly degrade the network's performance and under such scenario jammers will devastate the control channels. Hopping sequences may be one of the predominant approaches and it may be used to fight against this problem to confront jammer. The jamming attack can be alleviated using one of the game modelling approach and in this proposed scheme stochastic games has been analysed with more single users to provide the flexible control channels against intrusive attacks by mentioning the states of each player, strategies ,actions and players reward. The proposed work uses a modern player action and better strategic view on game theoretic modelling is stochastic game theory has been taken in to consideration and applied to prevent the jamming attack in CR network. The selection of decision is based on Q learning approach to mitigate the jamming nodes using the optimal MDP decision process

• 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.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.83-90
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• 2004

Strategic games are missing special qualities of genre these days. Game engines neither reason about behaviors of computer objects nor have learning ability that can prepare countermeasure in variously command user's strategy. This paper suggests a strategic game engine that applies non-monotonic reasoning and inductive machine learning. The engine emphasizes three components -“user behavior monitor”to abstract user's objects behavior,“learning engine”to learn user's strategy,“behavior display handler”to reflect abstracted behavior of computer objects on game. Especially, this paper proposes two layered-structure to apply non-monotonic reasoning and inductive learning to make behaviors of computer objects that learns strategy behaviors of user objects exactly, and corresponds in user's objects. The engine decides actions and strategies of computer objects with created information through inductive learning. Main contribution of this paper is that computer objects command excellent strategies and reveal differentiation with behavior of existing computer objects to apply non-monotonic reasoning and inductive machine learning.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.159-179
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• 2024

Based on the case of collaboration between large companies and startups, this study suggests the importance of establishing mutual cooperation and trust relationships for the success of open innovation strategy from the perspective of cooperative game theory. It also provides implications for how this can be implemented. Due to information asymmetry and differences in organizational culture and decision-making structures between large companies and startups, collaboration is likely to proceed in the form of non-cooperative games among players in general open innovation, leading to the paradox of open innovation, which lowers the degree of innovation. Accordingly, this study conducted a case study on collaboration between large company 'G' and startup 'S' based on the research question "How did we successfully promote open innovation through cooperative game-type collaboration?" The study found that successful open innovation requires (1) setting clear collaboration goals to solve the organizational problem between large companies and startups, (2) supporting human resources for qualitative growth of startups to solve reliability problems, (3) leading to strategic investment and joint promotion of new projects to solve the profit distribution problem. This study is significant in that it contributes to expanding the discussion of the success factors of open innovation to the importance of interaction and strategic judgment considering the organizational culture and decision-making structure among players, and empirically confirming the success conditions of open innovation from the perspective of cooperative game theory.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.75-83
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• 2015

In mobile ad-hoc networks (MANETs), nodes are mobile in nature. Collaboration between mobile nodes is more significant in MANETs, which have as their greatest challenges vulnerabilities to various security attacks and an inability to operate securely while preserving its resources and performing secure routing among nodes. Therefore, it is essential to develop an effective secure routing protocol to protect the nodes from anonymous behaviors. Currently, game theory is a tool that analyzes, formulates and solves selfishness issues. It is seldom applied to detect malicious behavior in networks. It deals, instead, with the strategic and rational behavior of each node. In our study,we used the dynamic Bayesian signaling game to analyze the strategy profile for regular and malicious nodes. This game also revealed the best actions of individual strategies for each node. Perfect Bayesian equilibrium (PBE) provides a prominent solution for signaling games to solve incomplete information by combining strategies and payoff of players that constitute equilibrium. Using PBE strategies of nodes are private information of regular and malicious nodes. Regular nodes should be cooperative during routing and update their payoff, while malicious nodes take sophisticated risks by evaluating their risk of being identified to decide when to decline. This approach minimizes the utility of malicious nodes and it motivates better cooperation between nodes by using the reputation system. Regular nodes monitor continuously to evaluate their neighbors using belief updating systems of the Bayes rule.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.945-956
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• 2013

The character industry is a high value-added industry, and is one of the strategic industries to be fostered. However, the character industry is struggling due to the lack of national consensus on the importance and value of the character industry. Therefore, in order to resolve this issue, the study used the character Input-Output Table of year 2009 of korea to analyze how much the character industry(Toys and games, Models and decorations) contributes to the national economy by measuring economic spreading effects of character industry on national economy. The results shows that character industry shows that production inducement coefficient is column 1.602, row 1.007, index of the sensitivity of dispersion is 0.543, Index of the power of dispersion is 0.864, value-added coefficient is 0.620, income inducement coefficient is 0.334, tax inducement coefficient is 0.066, employment inducement coefficient is 0.008.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1201-1207
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• 2016

Background: Excessive exposure to the sun during childhood is strongly associated with the development of skin cancer in the future. The only way to prevent the development of skin cancer is to protect against ultraviolet radiation, which can be achieved through strategic awareness during childhood and adolescence. Objective. The aim of this work was to evaluate the impact of educational activities for rural and urban students to promote the use of sunscreens and prevent skin cancer. Materials and Methods: This study was carried out with students (9-12 years) of rural (n=70) and urban (n=70) schools in Rio Grande do Sul state, Brazil. The educational interventions were lectures and games. The impact of this strategy was evaluated through the application of a questionnaire before and after the interventions. Results: Before the intervention, it was found around 50% of rural and urban students were not aware of the damage caused by sun exposure, often exposing themselves to UV radiation without use sunscreen ( ~ 25 %) and at the most critical times of the day/year. After the lectures we observed an improvement in the behavior of the students with regard to sun exposure and knowledge about skin cancer. Conclusions: The results of this study emphasize the importance of prevention strategies for skin cancer and promoting the use of sunscreens based educational strategies. The interventions were of great value in relation to disseminating knowledge on the subject.