• Journal of Korea Game Society
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• v.17 no.2
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• pp.17-26
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• 2017

Excessive use of the internet and smart phones have become a social issue. The level of engagement has both positive and negative effects such as good performance or indulgence phenomenon, respectively. This study was to develop an algorithm to determine the engagement state based on cardiovascular response. The participants were asked to play a pattern matching game and the experimental design was divided into cooperation and competition task to provide the level of engagement. The correlation between heart rate and amplitude was analyzed according to each task. The regression equation and accuracy were verified by polynomial regression analysis. The results showed that heart rate and amplitude were positively correlated when the task was a game, and negatively correlated when there was a reference task. The accuracy of classifying between game and reference task was 89%. The accuracy between tasks was confirmed to be 76.5%. This study is expected to be used to quantitatively evaluate the level of engagement in real time.

• Journal of Korea Game Society
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• v.6 no.4
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• pp.79-87
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• 2006

This paper proposes the design and implementation of engine to control characters by using machine teaming techniques. Because the proposed engine uses the context data in the rum time as the knowledge data, there is a merit which the player can not easily recognize the behavior pattern of the intelligent character. To do this, the paper proposes to develop the module which gathers and trains the context data and the module which tests to decide the optimal context control for the given context data. The developed engine is ported to FEAR and run with Quake2 and experimented far the correctness of the development and its efficiency. The experiments show that the developed engine is operated well and efficiently within the limited time.

• Journal of Korea Game Society
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• v.8 no.1
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• pp.103-113
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• 2008

Although people have had more opportunities to enjoy various types of game, most of players have felt less satisfaction with the games. This is the reason that since most Non-player Characters (NPCs) are simple and uniform, they have some limitations for competing with a variety of players. Thus, technologies for creating intelligent NPCs that can compete with each player at a similar level are required. In this paper, we present an action information management method for creating adaptive NPCs based on the algorithm for calculating their action efficiency. This algorithm is useful to the adaptation method for saving and controlling player-appropriate action. In our method, adaptive NPCs observe the actions of players and collect the relationship data between status and action. The efficiency value of the action data is calculated and data of similar status are grouped, and finally stored at the action database. The game system of NPC updates the action database and stores diverse actions. Then, NPC selects action with high efficiency value. We have tested our algorithm on an action game. A random test subject performed a one-on-one game against an adaptive NPC in real-time. As a result, the action dispositions of both the subject and NPC are analyzed in a log file to determine whether or not the disposition of the subject is similar to that of the NPC. The statistics of the diverse test results shows that NPCs become adaptive to players with error rate within less than 6%.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.289-293
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• 2002

Learning Classifier System (LCS) finds a new rule set using genetic algorithm (GA). In this paper, The Zeroth Level Classifier System (ZCS) is applied to evolving the strategy of a robot soccer simulation game (SimuroSot), which is a state varying dynamical system changed over time, as GBML (Genetic Based Machine Learning) and we show the effectiveness of the proposed scheme through the simulation of robot soccer.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.669-673
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• 1998

This paper makes a study of the Shapley value in cooperative fuzzy games, games with fuzzy coalitions, which enable the representation of players' participation degree to each coalition. The Shapley value has so far been introduced only in an class of fuzzy games where a coalition value is not monotone with respect to each player's participation degree. We consider a more natural class of fuzzy games such that a coalition value is monotone with regard to each player's participation degree. The properties of fuzzy games in this class are investigated. Four axioms of Shapley functions are described and a Shapley function of a fuzzy fame in the class is given.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.275-280
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• 2010

Verification of efficiency in data management fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem and numerical data similarity evaluation. In order to calculate the certainty or uncertainty fuzzy entropy and similarity measure are designed and proved. Designed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration. Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.89-92
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• 2004

로보코드는 사용자가 직접 제작할 수 있는 슈팅게임 환경으로서, 이를 이용한 경진대회가 개최되고 있다. 매우 다양한 작전을 구사하는 로봇들이 인터넷을 통해 공개되지만, 대부분의 전략은 사람이 직접 설계하여 행동이 단순하고, 변화하는 환경에 따라 행동을 구사하는데에 어려움을 가지고 있다. 이로 인해 아무리 훌륭한 전략을 가지고 있더라도 환경적 요소에 따라 예상치 못한 이벤트가 발생했을 경우 적절한 행동을 선택하여 행하기가 어렵다. 본 논문에서는 동적인 환경에서 적절한 행동을 선택하는 행동선택 네트워크를 이용하여 상대 전략에 따라 적절한 행동을 선택하는 방법을 제안하고 로보코드에 적용하여 실험하였다. 실험결과, 상대 탱크의 전략에 따라 다양한 행동들을 자동으로 선택하였으며, 경기 결과로 그 전략의 우수성이 입증되었다.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.229-235
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• 2003

We designed a family of completely autonomous mobile robots with local intelligence. Each robot has a number of on-board sensors, including vision, and does not rely on global positioning systems The on-board embedded controller is sufficient to analyze several low-resolution color images per second. This enables our robots to perform several complex tasks such as navigation, map generation, or providing intelligent group behavior. Not being limited to playing the game of soccer and being completely autonomous, we are also looking at a number of other interesting scenarios. The robots can communicate with each other, e.g. for exchanging positions, information about objects or just the local states they are currently in (e.g. sharing their current objectives with other robots in the group). We are particularly interested in the differences between a behavior-based approach versus a traditional control algorithm at this still very low level of action.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.170-177
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• 2010

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.85-88
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• 1998

진화이론은 생명체들간의 투쟁과 적자생존의 원칙에 근거를 두고 있다. 그 중 협동으로의 진화는 공생이나 기생관계에 있는 생물들에서 발견되어 사화학, 생물학, 경제학 등의 분야에서 계속적인 관심의 대항이 되어 왔다. 특히 생명체들간에 존재하는 끊임없는 경쟁과 협동의 관계를 시뮬레이션하는 죄수의 딜레마 게임은 지금까지 많은 연구가 진행되어왔다. 죄수의 딜레마 게임이 시작된 근거는 협동으로의 진화에 관한 연구에서 시작되었다고 볼 수 있다. 대부분의 연구가 2명이 하는 죄수의 딜레마 반복게임인 2IPD에 집중되어 있는데 2IPD는 실제 세계에 적용시키는데 한계가 있기 때문에 보다 실세계에 가까운 형태를 모델링하는 N명 죄수의 딜레마 반복 게임(NIPD)에 관한 연구가 진행되고 있다. 이 논문에서는 진화 알고리즘을 이용하여 NIPD게임에서 게임자의 수와 협동으로의 진화와의 관계, 즉 죄수의 수가 증가함에 따라 협동의 정도는 어떻게 나타나는 가에 대해 고찰한다. 여러차례의 반복 시뮬레이션 결과 게임자의 수가 적을때는 대부분이 협동으로 진화하나 게임자의 수가 증가할수록 협동으로의 진화가 어렵다는 사실을 확인할 수 있었다.