• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.65-70
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• 2001

We consider a hyper-redundant system that consists of many uniform units. The hyper-redundant system has many degrees of freedom and it can accomplish various tasks. Applysing the reinforcement learning to the hyper-redundant system is very attractive because it is possible to acquire various behaviors for various tasks automatically. In this paper we present a new reinforcement learning algorithm "Q-learning with propagation of motion". The algorithm is designed for the multi-agent systems that have strong connections. The proposed algorithm needs only one small Q-table even for a large scale system. So using the proposed algorithm, it is possible for the hyper-redundant system to learn the effective behavior. In this algorithm, only one leader agent learns the own behavior using its local information and the motion of the leader is propagated to another agents with time delay. The reward of the leader agent is given by using the whole system information. And the effective behavior of the leader is learned and the effective behavior of the system is acquired. We apply the proposed algorithm to a snake-like hyper-redundant robot. The necessary condition of the system to be Markov decision process is discussed. And the computer simulation of learning the locomotion is demonstrated. From the simulation results we find that the task of the locomotion of the robot to the desired point is learned and the winding motion is acquired. We can conclude that our proposed system and our analysis of the condition, that the system is Markov decision process, is valid.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.297-303
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• 2007

In this paper, we discuss a service to give alarm in the case of emergency for the old and the weak by human behavior recognition in Intelligent Space. Our Intelligent Space consists of mobile robots, sensors and agents. And these components are connected to network framework. Agent analyzes data acquired from networked sensors and determines task of robots and a space to provide a service for humans. In our emergency alarm service, human behavior recognition service module analyzes accelerometer data obtained from body-attached human behavior sensing platform, and classifies into four basic human behavior such as walking, running, sitting and falling-down. For the old and the weak, falling-down behavior may bring about dangerous situations. On such an occasion, agent executes emergency alarm service immediately. And then a selected mobile robot approaches fallen person and sends images of the person to guardians. In this paper, we set up a scenario to verify the emergency alarm service in Intelligent Space, and show feasibility of the service from our simulation experiments.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1335-1344
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• 2014

In architectural design, the user is one of the most important factors for the design task as well as the standard for evaluating the value of the built environment after its construction. Recently, accidents, such as fires and breakdowns, in huge and complicated buildings have increased the importance of user behavior simulation. The Korean government has tried to establish a regulation for the prevention of accidents in the built environment. This is regarded as a significant step forward for providing a safer and more appropriate environment for users. However, the existing technologies related to analyzing user behavior only simulate simplified situations. Such simulations are not enough to evaluate accurately the designed alternatives because buildings and spaces contain more complicated information than what we have conventionally considered. Thus, we propose that the advanced agent can interact with the architectural context. It can understand not only the physical situation but also how the users affect this situation. In order to realize this, we adopted the concept of affordances as the perceived action possibilities for the simulation environment.

• Journal of Information Technology Applications and Management
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• v.16 no.3
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• pp.17-28
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• 2009

This paper presents a novel method for evaluating the usefulness of online product recommendation. Previous studies on evaluating recommendation systems have mostly relied on two methods : testing the accuracy of estimating user preferences by recommendation systems, or empirically testing the effectiveness with lab experiments involving human participants. The former does not measure the usefulness directly and hence can be misleading; the latter is expensive in that it requires a working online store System and test participants. In order to address the problems, the proposed approach uses simulation to imitate customer behavior and evaluate the usefulness of recommendation. Models for user behavior and an abstract Internet store are developed for simulation. Actual simulation experiments are performed to illustrate the use of the approach.

• Journal of Korean Society of Rural Planning
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• v.27 no.2
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• pp.77-89
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• 2021

To predict the level of residents' participation in rural tourism project, we used agent-based model. The decision-making mechanism which calculates the utility related to attitude, subjective norm, perceived behavioral control of planned behavior theory was applied to the residents' decision to participate. As a result of the simulation over a period of 20 years, in the baseline scenario set similar to the general process of promoting rural projects, the proportion of indigenous people decreased and the participation rate decreased. In the scenarios with different learning frequencies in perceived behavioral control, overall participation rate decreased. Learning every five years had the effect of increasing the participation rate slightly. Participation rates increased significantly in the scenario that consider economic aspects and reputation in attitude and did not decline in the scenario where population composition was maintained. The virtuous cycle effect of subjective norm according to changes in participation rate due to influence of attitude and perceived behavioral control shows the dynamic relationship.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.117-125
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• 2009

Recently the intelligent agent systems have been emerged as one of key issues for developing the defense M&S systems. However, most conventional agent architecture of M&S systems utilize the script-based models and can only deal with the individual behaviors so that they cannot suitably describe the precise tactical/strategic behavior and/or complex warfare environment. To overcome these problems, we have proposed the hierarchical multi-agent system architecture that is able to intelligently cope with the complex missions based on the functional role of each agent on the hierarchy such as an intelligence officer, captain, warship commander. Several simulation tests performed on 2:2 warship warfare models will illustrate our techniques.

• Journal of Korea Game Society
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• v.8 no.1
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• pp.79-90
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• 2008

This paper describes a motivation-based hierarchical behavior planning framework to allow autonomous agents to select adaptive actions in simulation game environments. The combined behavior planning system is formed by four levels of specification, which are motivation extraction, goal list generation, action list determination and optimization. Our model increases the complexity of virtual human behavior planning by adding motivation with sudden and cumulative attributes. The motivation selection by probability distribution allows NPC to make multiple decisions in certain situations in order to embody realistic virtual humans. Hierarchical goal tree enhances the effective reactivity. Optimizing for potential actions provides NPC with safe and satisfying actions to adapt to the virtual environment. A restaurant simulation game was used to elucidate the mechanism of the framework.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.35-47
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• 2020

Immediate and serious attention on CGF(computer generated forces) behavior modeling for defense M&S (modeling & simulation) is required in response to the reduction in the number of troops and development of 4^th industrial technologies. It is crucial for both military person and engineer to understand such technologies. The research aims to provide guidelines for establishment of research direction on CGF behavior modeling. We investigate traditional and/or novel methodologies such as rule-based, agent-based, and learning-based method. Discussions on future direction of applicable area and strategies are followed. We expect that the research plays a key role for understanding CGF behavior modeling.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.194-205
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• 2006

The purpose of this study is to develop a pedestrian multi-agent model and simulation system using multi-agent theory, which may be utilized as a planning support system for building a comfort and safe environment of pedestrian street. Differing from existing pedestrian models, however, every single pedestrian was regarded as an individual agent in the model. Multiple agents like multiple pedestrians in the street then maintain their own characteristics and respond to surrounding environment. In addition their moving behavior are made by their own decision rules that they have or had acquired through the interactive communications or learning between agents like real world. After verifying the model validation, as the $R^2$ between the predicted value and observed value was up to 0.781, the developed model was applied to Gazwa district within Gyeongsang university village. The simulation system was developed by Flash MX action scripts and the physical environment of the streets was configured with the digital map and ArcGis within computer virtual space. The attribute data of buildings such as type and size of commercial business were collected through the field survey and combined with physical features. Then the effect of the variation of building attractiveness and the occurrence of street events to pedestrian environment were simulated. Through the experiments this study could make suggestions to improve pedestrian environment.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.71-79
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• 2020

As the urbanization trend in modern society continues, the concentration of the population induces the urban problems in the residential area. One of the well-known issues among various urban problems is the garbage problem, which causes deterioration of the residential environment of citizens and directly affects the satisfaction of municipal administration. Such garbage problem cannot be accurately predicted by analyzing the amount of waste emitted from residential areas, but it is necessary to analyze the lifestyle and characteristics of residents living in residential areas. In this study, we propose an agent-based residential modeling and simulation environment using discrete event system formalism to analyze the garbage problem and satisfaction level according to the distribution of residents in the residential area. To model the behavior of the residents, we utilized the Atomic Model to capture the temporal behavior. Also, we used the Coupled Model to model the multi-family and the building to enhance the reusability of the simulation model. Also, this study carried out simulation modeling and simulation for a multi-family residential area. The simulation results of the multi-family housing area show that considering the characteristics of the residents gives better results compared to the simulation results without considering the characteristics.