• The Mathematical Education
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• v.43 no.1
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• pp.87-96
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• 2004

For finding the optimal strategy in Blackout game which was introduced in the homepage of popular mono "Beautiful mind", we develope a mathematical proof and an algorithm with a software. We only use the concept of basis and knowledge of basic linear algebra. This process can be extended to the fullsize Go table problem and shows why we have to study mathematics at the college level.

• 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.

• Information Systems Review
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• v.23 no.1
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• pp.1-22
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• 2021

This study aims to analyze online game user's game items transacting behaviors for the two game genres such as MMORPG and sports game. For the sake of conducting the analysis, we adopted a fuzzy logic agent-based modeling. In the online game fields, game items transactions are crucial to game company's profitability. However, there are lack of previous studies investigating the online game user's game items transacting activities. Since many factors need to be addressed in a complicated way, ABM (agent-based modeling) simulation mechanism is adopted. Besides, a fuzzy logic is also considered due to the fact that a number of uncertainties and ambiguities exist with respect to online game user's complex behaviors in transacting game items. Simulation results from applying the fuzzy logic ABM method revealed that MMORPG game users are motivated to pay expensive price for high-performance game items, while sports game users tend to transact game items within a reasonable price range. We could conclude that the proposed fuzzy logic ABM simulation mechanism proved to be very useful in organizing an effective strategy for online game items management and customers retention.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.181-182
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• 2016

The game policy in China takes the way of promoting the development of domestic enterprises through protecting the growth of those. In order to improve the development of domestic game industry, it will maintain the policy that restrict the import of overseas game. However, as to the domestic enterprise, it will develop the aid policy in the form of encouraging overseas export. For the characteristics of wide audience, long life term and easy to be developed, the class game of flags and cartes has become a very significant field of game industry. But for the gamble characteristics of the class game of flags and cartes, it also becomes the center for the government of making regulations and policies. This research aims to analysis the china game policies for the class game of flags and cartes and to find the strategy to entry into the china.

• Journal of Korea Game Society
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• v.19 no.4
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• pp.49-64
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• 2019

In this paper, we examined the concept of three types of double loot box respectively and analyzed each characteristics of double loot box by game case study. Those types are divided into the following three cases; 1) Double-mileage gacha 2) Double-limited period gacha 3) Kompu gacha. As the result, Double loot boxs are characterized as below: 1) Double loot box has a tendency to combine various type of loot boxes. 2) Double loot box's reward is hard to gain in game, or not to sell in game store. With these features, double loot box could be a gambling sales strategy. To solve this problem, this study suggested that it is essential to revise game self-regulations, enhance the professionalism of monitoring groups, and propel the self-effort of game companies.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.14-20
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• 2019

Energy saving is becoming more and more important issue due to lack of resources and limited nature. However, There is a lack of learning status on energy saving in the school field. In particular, in elementary education on energy saving was not linked to practice, and the educational effect was insufficient. Although various kinds of learning tools are utilized, many successful cases of energy saving game strategy are introduced in overseas industry field, and game design is proposed so that energy related education can be played through games. Because energy conservation can not be effective without practice, learning using games as a tool is expected to be more effective than learning based on knowledge transfer in the classroom. We propose a defense game for energy conservation education by using the mission elements, score acquisition element, time limit element, and character element which are the interesting elements of the game designed in the previous research.

• Journal of Korea Game Society
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• v.13 no.3
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• pp.141-152
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• 2013

This research aims at suggesting a case of designing theme-based integrated learning for usage smart media. New approach and direction for developing a gaming instructional design was suggested which can encourage learners to participate in. Quest-based learning, the learning environment design where learners conduct various learner-centered activities, plays an important role of reinforcing the motivation, promoting experiential and cooperative learning based on social interaction. The design using QR codes has been proved to be able to offer the learner-centered learning environment which includes social interaction strategy required for learners expanding their cognitive structure, motivation enhancing strategy encouraging their consistent participation in learning, complex problematic situation and scaffolding strategy emphasized by constructivism. And it is expected to contribute to promoting the design of theme-based integrated learning which is being demanded in the educational environment recently by combining systematic design process and strategies.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.690-693
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• 2003

The purpose of two player game is that a player beats an enemy. In order to win to various enemies, a learning of various strategies is indispensable. However, the optimal action to overcome the enemies will change when the game done over and again because the enemy's actions also change dynamically. Sol it is din-cult that the player aquires the optimal action and that the specific player keeps winning to various enemies. Species who have a competition relation and affect other's existence is called a coevolution. Coevolution has recently attracred considerable interest in the community of Artificial Life and Evolutionary Computation(1). In this paper, we apply Classifier System for agent team to two player game. A reward and a penalty are given to the used rules when the agent achieve specific action in the game and each team's rulebase are evaluated based on the ranking in the league. We show that all teams can acquire the optimal actions by coevolution.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2854-2874
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• 2015

This paper presents a game theoretic approach to analyze the public goods (PGs) allocation in peer-to-peer (p2p) networks. In order to reduce the free-riders and promote the cooperation among peers, we propose an incentive mechanism with cooperation-based game theory. In this paper, we regarded the contributed resources by cooperators as public goods (PGs). We also build the PGs allocation in P2P networks to be the optimization problem, and the optimal solution of PGs allocation satisfies the Bowen-Lindahl-Samuelson equilibrium. Firstly, based on the subscriber mechanism, we analyze the feasibility and prove the validity, which can achieve Nash equilibrium. However, this strategy cannot meet to Bowen-Lindahl-Samuelson equilibrium as the free-riders do not pay with their private goods for consuming the PGs. Secondly, based on the Walker mechanism, we analyze the feasibility and prove the validity for the same allocation problem, which meets to Bowen-Lindahl-Samuelson equilibrium and achieves Pareto efficiency within cooperative game. Simulations show that the proposed walker mechanism can significantly improve the network performance of throughout, and effectively alleviate free-riding problem in P2P networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4157-4175
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• 2020

Moving target defense, as a 'game-changing' security technique for network warfare, realizes proactive defense by increasing network dynamics, uncertainty and redundancy. How to select the best countermeasure from the candidate countermeasures to maximize defense payoff becomes one of the core issues. In order to improve the dynamic analysis for existing decision-making, a novel approach of selecting the optimal countermeasure using game theory is proposed. Based on the signal game theory, a multi-stage adversary model for dynamic defense is established. Afterwards, the payoffs of candidate attack-defense strategies are quantified from the viewpoint of attack surface transfer. Then the perfect Bayesian equilibrium is calculated. The inference of attacker type is presented through signal reception and recognition. Finally the countermeasure for selecting optimal defense strategy is designed on the tradeoff between defense cost and benefit for dynamic network. A case study of attack-defense confrontation in small-scale LAN shows that the proposed approach is correct and efficient.