• Journal of Internet Computing and Services
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• v.11 no.3
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• pp.25-32
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• 2010

It takes quite amount of time to study a game because there are many game characters and different stages are exist for games. This paper used reinforcement learning algorithm for characters to learn, and so they can move intelligently. On learning early, the learning speed becomes slow. Improved sequential prediction method was used to improve the speed of learning. To compare a normal learning to an improved one, a game was created. As a result, improved character‘s ability was improved 30% on learning speed.

• The KIPS Transactions:PartA
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• v.19A no.1
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• pp.69-72
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• 2012

Logic programming based on classical or linear logic has traditionally lacked devices for expressing sequential tasks and sequential iterative tasks. Expressing sequential goal tasks has been addressed by a recent proposal of sequential goals of the form $G_1{\cap}G_2$ which is based on the game semantics of Japaridze. This paper proposes sequential iterative goal formulas of the form ${\cap}_x^LG$ where $G$ is a goal, $x$ is a variable, and $L$ is a list. ${\cap}_x^L$ is called a sequential bounded quantier. These goals allow us to specify the following task: sequentially iterate $G$ with $x$ ranging over all the elements of $L$.

• Korea Trade Review
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• v.46 no.5
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• pp.1-12
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• 2021

In 2009, Japanese government requires exporters to have individual export licenses for certain items and removes South Korea from White Countries. The export control and regulations are likely to be affected by political factors. This study aims to analyze Japan-South Korea trade dispute with a sequential game with incomplete information. The results show that Japan may apply trade regulations on Korea regardless of efficiency of Korea and the possibilities of regulations increases when political factors are important in its decision on export policy.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.259-264
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• 2019

In this paper, the prototyping process for developing syllable-initial consonant-based game 'Korean Guards' is described. Users may effectively learn Korean words using alphabetically sequential approaches, but the easiness of access bestowed on the smart environments and game algorithms could be fully utilized for the functional advantages for educational purposes. This functional game is developed on Android OS and the prototypical outcome is shown.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.141-149
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• 2011

The substantial effort is required to make a virtual character smoothly move like a human being in the virtual environment. Since a virtual character acts on the basis of the actions, it is the most critical to define actions for smooth flow of action. It has been actively studied the programming by demonstration which defines series of actions to be performed by a virtual character based on the actions operated by a person. However, such approaches can't easily draw many sequential actions because they create sequential actions in the same length all the time or restrict the actions used to create such actions. For smooth flow of action, it is required to derive sequential actions as much as possible from the actions of a virtual character and to select the representative set of actions. Accordingly, it is necessary to study how to create sequential actions as reducing diverse limits. This study suggests the approach to select sequential actions suitable for a virtual character by collecting the actions of a character manipulated by a person and deriving a set of actions to be performed by a virtual character. The experiment describes the process to create the actions by applying the approach suggested in this study to the driving game. In accordance with the analysis results, it was found that a set of actions performed by a person was generated without being restricted by a length or a part to divide. Finally, we confirmed that the suggested method selects the best sequential actions, appropriate to virtual character, among more generated actions.

• Environmental and Resource Economics Review
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• v.27 no.1
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• pp.1-28
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• 2018

This study investigates the strategic environmental corporate social responsibility (ECSR) of polluting duopoly when two firms have different production costs and compete with prices. We then examine an endogenous timing game in choosing ECSR and its effects on environmental damage and social welfare. The followings are the main findings: First, sequential choice of ECSR is strategic complements and it provides late adopter advantage irrespective of cost difference. Second, sequential choice of ECSR is the equilibrium of endogenous timing game. In particular, an efficient firm-leading ECSR is the payoff dominance equilibrium when cost difference is significant. Finally, environmental damage and social welfare depend on the social cost of pollution. In particular, an efficient firm-leading ECSR is socially desirable when social cost is high. However, an inefficient firm-leading ECSR increases environmental damage irrespective of social cost and it reduces social welfare when cost difference is significant.

• Journal of Korea Port Economic Association
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• v.29 no.4
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• pp.73-95
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• 2013

This paper analyzes a competitive shipping market in East Asia in order to explore how container carriers make decisions on ship size, number of ships, service frequency, and service route. A sequential-move game based on non-cooperative game theory is applied to establish the models for the decision-makings involving the transportation volumes, freight rates, costs, and market shares of the service routes from Shanghai or Hong Kong to the ports in Busan, Gwangyang, and Incheon. According to the sub-game perfect Nash equilibrium solutions proposed by these models, carriers' decisions in such a competitive environment vary depending on sailing distance, transport demand, and freight rates. Therefore, carriers are recommended to reflect the optimal equilibrium solutions and a variety of decision factors when formulating strategies for transportation networks and operating fleets. Furthermore, ports should establish management strategies for these factors to provide optimal equilibrium solutions for carriers' transportation networks.

• Korean Journal of Child Studies
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• v.21 no.3
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• pp.25-40
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• 2000

This study investigated the development of infant behaviors and maternal scaffolding in mother-infant games. Subjects were 60 mothers and their 9-, 12-, 15- and 18-month infants, 15 dyads in each age group. Mother-infant interaction was videotaped in the laboratory as they played peek-a-boo and a ball game in 2 sessions. Infant game behaviors were classified by the Rome-Flanders, Cossette, Ricard and $D{\acute{e}}carie$(1995) list, and maternal game behaviors were classified by the Hodapp, Goldfield & Boyatzis(1984) list. Data were analyzed by one-way ANOVA, two-way ANOVA with repeated measures, sequential analysis and Z test as well as qualitative analysis. Results showed that infants played an increasingly active role with age. Infants mastered the ball game at earlier age than peek-a-boo. Mothers scaffolded infant behaviors in various ways. The amount of maternal game behavior varied by type of game.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1820-1831
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• 2010

When interacting with unknown environments, an autonomous agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. The traditional multiple sequential learning model requires predefined probability of the states' transition. This paper proposes a multiple sequential learning and prediction system with definition of autonomous states to enhance the automatic performance of existing AI algorithms. In sequence learning process, the sensed states are classified into several group by a set of proposed motivation filters to reduce the learning computation. In prediction process, the learning agent makes a decision based on the estimation of each state's cost to get a high payoff from the given environment. The proposed learning and prediction algorithms heightens the automatic planning of the autonomous agent for interacting with the dynamic unknown environment. This model was tested in a virtual library.

• Journal of the military operations research society of Korea
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• v.14 no.1
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• pp.63-83
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• 1988

This study is concerned with the equilibrium bidding strategy and the optimal auction design of sequential auction with a reserve price and an entry fee. It is assumed that each bidder has a fixed reservation value and draws the reservation values of other bidders independently in the same distribution and may obtain at most one object to be sold. Under such assumptions, the sequential auction will be analyzed by the game theoretic approach. The purpose of this paper is, in the sequential auction, to find the equilibrium bidding strategy and to design the optimal auction under the equilibrium bidding strategy. The equilibrium bidding strategy and the optimal auction design are further analyzed with respect to change of the reserve price, the entry fee, and the number of bidders and objects. Specially, the auctioneer's expected revenue for each auction is obtained and analyzed.