• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.21-30
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• 2007

Simulation means modeling structures or behaviors of the various objects, and experimenting them on the computer system. And the major approaches are DEVS(Discrete Event Systems Specification). Petri-net or Automata and so on. But, the simulation problems are getting more complex or complicated these days, so that an intelligent agent-based is being studied. In this paper, we are describing an intelligent agent-based simulation tool, which can supports the simulation experiment more efficiently. The significances of our system can be described as follows. First, the system can provide some AI algorithms through the system libraries. Second, the system supports simple method of designing the simulation model, since it's been built under the Finite State Machine (FSM) structure. And finally, the system acts as a simulation framework by supporting user not only the simulation engine, but also user-friendly tools, such as modeler scriptor and simulator. The system mainly consists of main simulation engine, utility tools, and some other assist tools, and it is tested and showed some efficient results in the three different problems.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.306-312
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• 2001

In this research, we are trying to develop a framework to evaluate the prevention program for Tsunami disaster based on the Multi-agent simulation model. Tsunami has arisen by the earthquake. It happened after flew minutes or few hours when it occurred. It is clear that Tsunami will come after earthquake and from seashore. If we prevent the damage by Tsunami, we should make people who is in the seashore and lived near the seaside escape from there. Moreover we must forecast the escape activity from Tsunami. Former research of this field, some researches try to forecast the escape activity as macro level. However, people who escape from Tsunami is differ from their physical ability and ability of information processing. It needs a more accuracy model to forecast the escape activity of them. Furthermore they make a decision step by step using the various information. Therefore escape activity from Tsunami will describe using an agent based model which can only treat the information processing of human being. In this paper, we develop the evacuation model from Tsunami disaster using the Multi agent based model. The purpose of this study is to analyze the human action pattern when Tsunami occurred, and to make an accurately assessment for damages by Tsunami. The Fujisawa city government is planning and operating the various prevention program far Tsunami. However nobody assess it, because they do not have any simulation models for Tsunami disaster. If they want to set an effective prevention program for Tsunami, they should have any kinds of simulation model. The results of this study are 1) To develop the Multi agent based evacuees escape activity model. 2) Assess the damage of Tsunami in Fujisawa-City.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.111-117
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• 2011

This paper suggests the passenger model considered evacuation behavioral characteristics on the passenger ship fire using a rules-based agent technique. The existing evacuation simulation system was modeled only passenger speed. The speed-based model considered passenger's physical characteristics, so it couldn't consider evacuation behavioral characteristics. For solving this problem, we modeled the passenger model using a rule-based agent applied evacuation behavioral characteristics. The rule-based agent consists of knowledge base and inference engine. In knowledge base, we represented evacuation behavioral characteristics, and chose the examples of the evacuation behavioral characteristics to show various patterns of behavior. And we simulated in the IMO MSC/Circ.1238 example 8 and we proved the simulation results could represent variety patterns of human behavior.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.149.5-149
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent´s dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless ...

• Journal of the Korea Society for Simulation
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• v.16 no.3
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• pp.39-48
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• 2007

This study suggests a method of command and control in modeling a combat situation. In particular, it presents the structure of an intelligent agent that may substitute for the current system of decision making in the military operation to lead a troop. Today the Korean military war game simulations emphasize on engagements, instead of command and control. This suggested principle will be a good foundation for the today and the future Korean warfare.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.165-180
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• 2019

As game industry prospers, the negative side of games becomes highlighted as well as its contributions to economy growth. In spite of strong arguments for the necessity to regulations as a means to decrease addiction or overindulgence, research has produced future suggestions rather than quantifiable evidence. In this paper, we propose adopting a simulation approach in addition to quantitative approaches to better understand optimal regulatory levels since a simulation approach can visualize unexpected side effects of regulations. In this study, we suggest the application of an agent-based model (ABM) as a smart service to measure the effects of regulatory policies. We review cases applying ABM in various domains and consider the possibility of using an ABM to understand the effectiveness of web board-game regulations. We find that the ABM approach would be useful in several areas, such as the analysis of regulatory effects that reflect a variety of characteristics, the measurement of micro-regulatory effects, and the simulation of regulations.

• Journal of KIISE
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• v.42 no.12
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• pp.1503-1521
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• 2015

Agent-based modeling and simulation (ABMS) is used to model of market and social phenomena by utilizing agents' fine-grained behaviors and interactions that cannot be implemented in a conventional simulation. However, ABMS represents irrational agents and hinders the achievement of individual or overall goals since ABMS is based on agent-based software, which follows the principle of rationality at the knowledge level [1]. This problem was solved in the agent-based software engineering (ABSE) field by using behavior laws for the social level [2]. However, they still do not propose the specific development methodology for how to develop the social level in a systematic way. Therefore, in order to propose agent-based modeling and simulation methods that reflect the behavior laws of social level characteristics, our study used the Tropos that can combine ABSE and social behavior laws for the presentation of concrete tasks and deliverables for each development step by step. In addition, the proposed method will be specified through experiments with specific application examples and case studies on the self-adaptive smart grid and the military domain system.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.101-109
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• 2011

M&S in the field of national defense is a battle system has been highly spotlighted for obtaining weapon systems, analyzing and experimentation of battle effects to reduce costs, time, and risks. It is classified as Campaign, Mission, Engagement, and Engineering levels by detail of description. In engagements, many situations on the battle field which are really unpredictable are required to be considered on the view of diverse tactics. Thus, engagement simulation is in demand to use for forecasting real-world battle situations by inserting various components which consists of real engaging situations into virtual local battle field. While developing the engagement simulation, adopting the concept of agent-based simulation gives it benefits which are improved autonomy, composability, and reusability of entities. It means reducing the time, cost and effort to develop the simulations. This paper concentrates on the framework of multi-agent based engagement simulation using Cougaar Architecture.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.169-178
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• 2010

Agent based simulation is an approach for the analysis of a system's long term behavior where the entities in the system behave independently by their own judgement and memory, but influence each other to cope with given environment. In this paper we developed an agent based simulation model for the analysis of behavioral mechanism of team formation. In the process of team formation members' mutual preference is an important factor although each member can join up with one's own will. Also a team performance can vary by the member's own experience. We implemented the developed model using Netlogo 4.1, and verified the model by simulation. From the simulation results we found that the model successfully performed necessary functions using behavioral rules, judgments, and evolutionary processes by memory. As a further study we will be able to apply the model for analyzing various ecological behavior of team formation.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.103-116
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• 2010

In this paper, we propose an optimal camera placement using agent-based simulation. To derive importance of space and to cover the space efficiently, we accomplished an agent-based simulation based on classification of space and pattern analysis of moving people. We developed an agent-based camera placement method considering camera performance as well as space priority extracted from path finding algorithms. We demonstrate that the method not only determinates the optimal number of cameras, but also coordinates the position and orientation of the cameras with considering the installation costs. To validate the method, we compare simulation results with videos of real materials and show experimental results simulated in a specific space.