• Journal of Information Processing Systems
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• v.18 no.6
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• pp.770-783
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• 2022

Early evacuations reduce the damage caused by catastrophic events such as terrorism, tsunamis, heavy rains, landslides, and river floods. However, even when warnings are issued, people do not easily evacuate during these events. To shorten the evacuation time, initiative-evacuation and its executors, initiative evacuees, are crucial in inducing other evacuations. The initiative evacuees take the initiative in evacuating and call out to their surroundings. This paper proposes a fast method to induce initiative-evacuation based on social graphs. The candidates are determined in descending order of the number of links for each person. The proposed method was evaluated through simulations. The simulation results showed a significant reduction in evacuation time.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1847-1854
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• 2005

This paper proposes a approach to configure efficient video-on-demand system by introducing Multicast and Cache Video-on-Demand (MCVoD) system. As a key element or the MCVoD system, interchange agent provides this system with multicasting and switching functions. With the multicasting, the MCVoD system is able to reduce the load on the network as well as VoD servers by transmitting only one video request instead of sending multiple requests on a same video stream. The switching enables clients to receive the lust stream of requested video streams instantly without waiting time and also allows avoiding undesirable duplication of video streams in the system. With various experiment results through simulation about waiting tine and cache hit ratio, we show that the MCVoD system employing the interchange agent provides better performance than current uni-proxy based system.

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.163-173
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• 2012

PURPOSES : The purpose of this study is to check the possibilities of traffic pattern analysis using MatSIM for urban road network operation in incident case. METHODS : One of the stochastic dynamic models is MatSIM. MatSIM is a transportation simulation tool based on stochastic dynamic model and activity based model. It is an open source software developed by IVT, ETH zurich, Switzerland. In MatSIM, various scenario comparison analyses are possible and analyses results are expressed using the visualizer which shows individual vehicle movements and traffic patterns. In this study, trip distribution in 24-hour, traffic volume, and travel speed using MatSIM are similar to those of measured values. Therefore, results of MatSIM are reasonable comparing with measured values. Traffic patterns are changed according to incident from change of individual behavior. RESULTS : The simulation results and the actual measured values are similar. The simulation results show reasonable ranges which can be used for traffic pattern analysis. CONCLUSIONS : The change of traffic pattern including trip distribution, traffic volumes and speeds according to various incident scenarios can be used for traffic control policy decision to provide effective operation of urban road network.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.271-280
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• 2010

While the future warfare is expected to be appeared as network-centric, effect-based, and coordinated cooperative, most current M&S systems reflect only the unit behaviors and interactions of each weapon system. There are limitations to analyze the behaviors of managing weapons cooperatively and sharing the situational awareness over the networks of distributed sensors, C2, and shooters using them. Therefore, we introduce the new design of the networkcentric warfare modeling system using the agent-based modeling and simulation approach. We have developed a system for engagement-level warfare models and tested with multi-platform battleship warfare. In this paper, we propose the method to design battle agents, environments, and networks for network centric warfare modeling.

• International Journal of Contents
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• v.12 no.1
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• pp.25-43
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• 2016

An agent-centric event planning method is proposed for providing pedagogical experiences in an immersed environment. Two-level planning is required at in a macro-level (i.e., inter-event level) and an intra-event level to provide realistic experiences with the objective of learning declarative knowledge. The inter-event (horizontal) planning is based on search, while intra-event (vertical) planning is based on hierarchical decomposition. The horizontal search is dictated by several realistic types of association between events besides the conventional causality. The resulting schematic plan is further augmented by conditions associated with those agents cast into the roles of the events identified in the plan. Rather than following a main story plot, all the events potentially relevant to accomplishing an initial goal are derived in the final result of our planning. These derived events may progress concurrently or digress toward a new main goal replacing the current goal or event, and the plan could be merged or fragmented according to their respective lead agents' intentions and other conditions. The macro-level coherence across interconnected events is established via their common background world existing a priori. As the pivotal source of event concurrency and intricacy, agents are modeled to not only be autonomous but also independent, i.e., entities with their own beliefs and goals (and subsequent plans) in their respective parts of the world. Additional problems our method addresses for augmenting pedagogical experiences include casting of agents into roles based on their availability, subcontracting of subsidiary events, and failure of multi-agent event entailing fragmentation of a plan. The described planning method was demonstrated by monitoring implementation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.462-467
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• 2005

This paper presents virtual machining system in order to realize turning process in virtual space. A reliable virtual turning process simulation was developed based on the surface shaping system which is capable of considering geometric model, thermal error model, and vibration model. Accuracy of surface shape resulting from proposed machining simulator was verified experimentally. This paper also developed the watchdog agent that continuously assessed, diagnosed, and predicted performance of products and machines in machining. The Watchdog agent extracted feature signal using time-frequency analysis among various signals from multi-sensor and evaluated machining condition using performance confidence value.

• Journal of Korean Society of Transportation
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• v.36 no.3
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• pp.169-183
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• 2018

Aggressive driving leads to a greater crash potential because it threatens surrounding vehicles. This study conducted traffic simulation experiments using driving behavior data obtained from multi-agent driving simulations. VISSIM traffic simulator and surrogate safety assessment model (SSAM) were used to identify the impacts of aggressive driving on traffic stream in terms of safety and operational efficiency. Market penetration rates (MPR) of aggressive driving vehicle, coupled with various traffic conditions, were taken into consideration in analyzing the impacts. As expected, it was identified that aggressive driving vehicles tended to deteriorate the traffic safety performance. From the perspective of operational efficiency, interesting results were observable. Under level of service (LOS) A, B, and C, it was observed that the average travel speed increased with greater MPRs. Conversely, the average travel speed decreased with under LOS D and E conditions. The outcome of this study would be effectively used for developing safety-related policies for reducing aggressive driving behavior.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.119-127
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• 2014

Recently, various methods derived from the experiences and the practices to manage knowledge have been proposed. However, the effects of the most of those methods have not been demonstrated quantitatively, but only the successful cases reported. In this paper, a method for knowledge transfer in a group is proposed to evaluate the effect of knowledge management and to express a shape that knowledge is transferred in the group by the multi-agent simulation. Simulation results show that the performance of the entire group is improved by introducing a knowledge database and a knowledge manager. In addition, the experience knowledge of the entire group is shown to be lost by reviewing results of the social issues by the proposed method. As a countermeasure for that, it was confirmed that the introduction of the knowledge database and the knowledge manager is more effective than those of an extension of the retirement age and of an increase of the intermediate recruitment.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.301-307
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• 2003

A control system design based on coupled nonlinear oscillators (CNOs) for a self- organized swarm system is presented. In this scheme, agents self-organize to flock and arrange group formations through attractive and repulsive forces among themselves using CNOs. Virtual agents are also used to create richer group formation patterns. The objective of the swarm control in this paper is to follow a moving target with a final group formation in the shortest possible time despite some obstacles. The simulation results have shown that the proposed scheme can effectively construct a self-organized multi-agent swarm system capable of group formation and group immigration despite the emergence of obstacles.