• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.3
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• pp.63-72
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• 2015

This paper presents the issue that is predicting the movement of an agent in an enclosed space by using the MDP (Markov Decision Process). Recent researches on the optimal path finding are confined to derive the shortest path with the use of deterministic algorithm such as $A^*$ or Dijkstra. On the other hand, this study focuses in predicting the path that the agent chooses to escape the limited space as time passes, with the stochastic method. The MDP reward structure from GIS (Geographic Information System) data contributed this model to a feasible model. This model has been approved to have the high predictability after applied to the route of previous armed red guerilla.

• Journal of Korea Game Society
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• v.19 no.6
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• pp.5-14
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• 2019

In this paper, we propose a modeling and simulation of group behavioral movement of pedestrians using Agent based and Cellular Automata model in intelligent game environment. The social behaviors of the crowds are complex and important, and based on this, the prototype game-model was implemented to show the crowd interaction on AB and CA in the game environment. Our experiment revealed the promise of group behaviour as a cost-efficient, yet accurate platform for researching crowd behaviour in risk situations with real models.

• 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 Korean Association for Spatial Structures
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• v.21 no.2
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• pp.41-48
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• 2021

A smart tuned mass damper (TMD) is widely studied for seismic response reduction of various structures. Control algorithm is the most important factor for control performance of a smart TMD. This study used a Deep Deterministic Policy Gradient (DDPG) among reinforcement learning techniques to develop a control algorithm for a smart TMD. A magnetorheological (MR) damper was used to make the smart TMD. A single mass model with the smart TMD was employed to make a reinforcement learning environment. Time history analysis simulations of the example structure subject to artificial seismic load were performed in the reinforcement learning process. Critic of policy network and actor of value network for DDPG agent were constructed. The action of DDPG agent was selected as the command voltage sent to the MR damper. Reward for the DDPG action was calculated by using displacement and velocity responses of the main mass. Groundhook control algorithm was used as a comparative control algorithm. After 10,000 episode training of the DDPG agent model with proper hyper-parameters, the semi-active control algorithm for control of seismic responses of the example structure with the smart TMD was developed. The simulation results presented that the developed DDPG model can provide effective control algorithms for smart TMD for reduction of seismic responses.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.221-225
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• 2015

To hoist construction workers to their working space is directly related to the productivity of building construction since hoisting tasks are carried out during the working time. In order to reduce hoisting time in the condition that the number of construction lift-cars is limited, various types of the lift-cars group operation plans such as zoning and sky-lobby have been applied. However, previous researches on them cannot be compared in the performance due to their methodological limitation, discrete-event simulation methods, and cannot be find better solution to increase the performance. Therefore, this research proposed the simulation-based optimization model combining the agent-based simulation method to the scatter search optimization methods. Using the proposed model, this paper carried out the comparison analysis on the performance of typical operation plans and also optimize an operation plans by controlling the service range of lift-cars, the size and number of service zones. In this case study, it is verified that better alternatives than typical operation plans can be exists and it is possible to increase the productivity of building construction.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.147-154
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• 2024

The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.435-436
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• 2012

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.69-78
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• 2015

Recently, research on the multi-agent system is developed actively in the various fields, especially on the control of complex system and optimization. In this study, we develop a multi-agent system for NPC simulation in game environment. The purpose of the development is to support quick and precise decision by inferencing the situation of the dynamic discrete domain, and to support an optimization process of the agent system. Our approach employed Petri-net as a basic agent model to simplify structure of the system, and used fuzzy inference engine to support decision making in various situation. Our experimentation describes situation of the virtual battlefield between the NPCs, which are divided two groups, such as fuzzy rule based agent and automata based agent. We calculate the percentage of winning and survival rate from the several simulations, and the result describes that the fuzzy rule based agent showed better performance than the automata based agent.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3417-3426
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• 2000

Most of conventional mobile agent systems requre that the users or the programmer should give the mobile agenl its detail behavioral script for accomplishing the given task. And during its runtime, such mobile agents just behave acording to the fixed script given by its user. Therefore it is impossible that conventional mobile agents autonomously build their own plans and execute. There in considering their ultirnale goals and the dynamic world states. One way to overcome such limtations of conventional mobile agent systems is to develop an mielligent mobile agent system ombedding a reactive planner.In this paper, we design both a modelof agent inobility and a model of inter-agent commuication based upon the representative reactive planning agent architecture called JAM. An then we develop an intelligent mobile agent system with planing capability, IMAS, by implementing addtional basic actions for agent moves and inter-agent comunication within JAM according too the predevined models. Unlike conventional mobile agents, IMAS agents can be able to adapt, their behaviors to the dynamic changes of their anvironment as well as build their own plans autonomously. Thus IMAS aents can snow higher flexibility and robustness than the conventional ones.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.101-115
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• 2009

The prompt recovery of housing market in Korea became the national task, for which tools that can analyze the influence that changing situation of housing market and new policy may have on the housing market needs to be developed. Thus, this research intends to develop Multi-Agent Housing Market Model and simulation system in Jinju City as a study area. Analyzing the local housing market of Jinju City, then multi-agent model of housing market that consolidates 3 sub-models, house choice model, hedonic model of house price and location choice model is developed. Moreover in order to develop simulation system the model is programmed in the virtual space of which the size is $150{\times}100$ cell including physical shape of city such as road, urban facilities, land use, etc. With the system, simulations are performed to confirm the impact of urban development on the pattern of residential location. As a result, it is found that the residential location can not be easily induced when only road, commercial and convenient facilities are supplied. However, it is also found that since supplying green results in very many residences, arrangement of infrastructure and environmental factor should be considered at the same time for urban development. As conclusion, it is confirmed that the model and simulation system developed in this research smoothly works to be utilized for the analysis of diverse policy experiment and housing market.