• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.22-28
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• 2015

In this paper, we studied the evolution of behavioral logic of artificial individuals using cell-level evolution framework. We first implemented cell-level evolution framework and then investigated the evolution of behavioral logic that artificial individuals ate foods on the framework. A logic frame for behavioral decisions of artificial individuals was devised and applied to the framework. From extensive tests, we found that most artificial individuals could evolve the behavioral logic that they could eat food in a short generation. It was also confirmed that most behavioral logics showed nearly same behaviors of artificial individuals in most tests. Our method has the differences from existing algorithms using evolutionary algorithms and evolvable hardwares in that it is a basically different approach. These results showed that our framework could be a good tool for investigating the evolution of artificial individuals in a cell-level.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.3-6
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• 2004

본 논문에서는 퍼지 로직을 이용하여 로봇과 공의 상태에 따른 로봇 행동의 선택 알고리즘을 제시한다. 전략 및 전술 알고리즘으로 많이 알려진 Modular Q-학습 알고리즘은 개체의 수에 따른 상태수를 지수 함수적으로 증가시킬 뿐만 아니라, 로봇이 협력하기 위해 중재자 모듈이라는 별도의 알고리즘을 필요로 한다. 그러나 앞으로 제시하는 퍼지 로직을 적용한 로봇축구 전략 및 전술 알고리즘은 퍼지 로직을 이용하여 로봇의 주행 알고리즘을 선택하는 과정과 로봇의 행동을 협력하는 과정을 동시에 구현함으로써, 계산 양을 줄여 로봇 축구에 보다 적합하게 해준다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.317-320
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• 2005

본 논문에서는 퍼지 로직을 이용하여 로봇의 여러 환경변수에 따라 로봇들의 행동을 적절히 선택하는 알고리즘을 제시한다. 전략 및 전술 알고리즘으로 많이 알려진 Modular Q-학습 알고리즘은 개체의 수에 따른 상태수를 지수 함수적으로 증가시킬 뿐만 아니라, 로봇이 협력하기 위해 중재자모듈이라는 별도의 알고리즘을 필요로 한다. 그러나 앞으로 제시하는 로봇 행동의 퍼지 적정성을 고려한 로봇축구 전략 및 전술 알고리즘은 환경 변수에 따라 로봇 행동의 적절성을 퍼지 로직을 통하여 얻어내게 하였으며, 이를 이용함으로써 다수 로봇의 상호작용도 고려할 수 있게 하였다.

• Journal of Navigation and Port Research
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• v.31 no.8
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• pp.725-731
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• 2007

This paper aims to analyze an action about a port choice of shipper between two ports. For this propose, this paper analyzed a port choice action for Kwangyang and Busan port using a fuzzy logic and neural network. Also, this paper compared classification performance of fuzzy-neural network to Logit model, and analyzed a port choice action into change Para-meta such as freight volumes and service standard.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.79-85
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• 2006

This paper presents a strategy and tactic for robot soccer using furry logic mediator that determines robot action depending on the positions and the roles of adjacent two robots. Conventional Q-learning algorithm, where the number of states increases exponentially with the number of robots, is not suitable for a robot soccer system, because it needs so much calculation that processing cannot be accomplished in real time. A modular Q-teaming algorithm reduces a number of states by partitioning the concerned area, where mediator algorithm for cooperation of robots is used additionally. The proposed scheme implements the mediator algorithm among robots by fuzzy logic system, where simple fuzzy rules make the calculation easy and hence proper for robot soccer system. The simulation of MiroSot shows the feasibility of the proposed scheme.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.971-980
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• 2010

In this paper, we present a navigation control algorithm for mobile robots that move in environments having static and moving obstacles. The algorithm includes a global and a local path-planning algorithm that uses $D^*$ search algorithm, a fuzzy logic for determining the immediate level of danger due to collision, and a fuzzy logic for evaluating the required wheel velocities of the mobile robot. To apply the $D^*$ search algorithm, the two-dimensional space that the robot moves in is decomposed into small rectangular cells. The algorithm is verified by performing simulations using the Python programming language as well as by using the dynamic equations for a two-wheeled mobile robot. The simulation results show that the algorithm can be used to move the robot successfully to reach the goal position, while avoiding moving and unknown static obstacles.

• Journal of Korea Game Society
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• v.2 no.2
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• pp.60-65
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• 2002

In the majority of today's computer games, the behaviour of characters are controlled by pre-defined game logic or pre-generated motion. As game developers strive for richer and more interactive games, they often encounter limitations with this approach. This paper attempts to construct a game model using Genetic Algorithms (GAs) in order to produce more intelligent and compelling computer games. Based on teaming ability, the use of GAs will enable the characters to continually evolve, providing a changing and dynamic game environment. A real-time game was implemented to investigate the performance and limitations of the system.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.144-146
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• 2012

의사결정표는 의사결정의 표현 방식 중 하나로 상황에 따라 취하는 일련의 행동들을 표 형식으로 나타낸 것이다. 이러한 의사결정표는 기업의 정보 시스템 (Information System)과 같은 의사결정 기반 시스템 구축에 유용하게 쓰일 수 있다. 복잡한 업무를 위한 의사결정 프로세스를 의사결정표를 이용하여 나타냄으로써 복잡한 로직을 정확하게 표현할 수 있고, 이해하기 쉽기 때문에 사용자와 프로그래머간의 의사소통을 원활하게 하며 문서화 작업을 비교적 간단하게 한다. 그러나 복잡한 의사결정이 필요한 업무의 경우 하나의 의사결정표에 필요한 정보를 모두 나타내게 되면 의사결정 단계를 이해하기가 어려울 뿐만 아니라 오류의 발생률도 높아지게 된다. 본 논문에서는 이러한 복잡한 의사결정을 돕기 위해 계층적인 의사결정표를 제안한다. 계층적 의사결정표는 여러 추상화 단계를 가진 의사결정표를 일관성 있게 표현함으로써 단계적으로 의사결정을 수행할 수 있게 하고, 이에 따라 의사결정에 대한 이해도를 높인다. 또한 기존의 의사결정표 지원 도구를 확장하여 계층적 의사결정표를 지원하는 도구를 개발함으로써 사용자의 편의성을 도모하였다.

• 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.

• Journal of the Korea Computer Industry Society
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• v.2 no.10
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• pp.1309-1316
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• 2001

In the majority of todays animation and computer games, the behaviours of characters are controlled by pre-defined game logic or pre-generated motion. As game developers strive for richer and more interactive games, they often encounter limitations with this approach. This paper attempts to construct a game model using Genetic Algorithms (GAs) in order to produce more intelligent and compelling computer games. Based on learning ability, the use of GAs will enable the characters to continually evolve, providing a changing and dynamic game environment. A real-time game was implemented to investigate the performance and limitations of the system.