• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.378-384
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• 2008

The sensor network for the health care application service has the man or movable object as the main sensing object. In order to support inter-node interaction by the movement of such sensing objects, the node's dynamic function modification, dynamic self-configuration and energy efficiency must be considered. In this paper, the Agilla model which supports the dynamic function modification through the agent migration between nodes and LEACH protocol which guarantees the dynamic self-configuration and energy efficiency through the configuration of inter-node hierarchical cluster configuration are analyzed. Based on the results of the analysis, the Mobility Agent Middleware which supports the dynamic function modification between nodes is designed, and LEACH_Mobile protocol which guarantees the node nobility as the weakness of the existing LEACH protocol is suggested. Also, the routing module which supports the LEACH_Mobile protocol is designed and the interface for conjunction with Mobility Agent Middleware is designed. Then, it is definitely increase performance which un mobility node of transfer data rate through LEACH_Mobile protocol of simulation result.

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.293-310
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• 2024

In this paper, we propose an agent model for Language-Driven Zero-Shot Object Navigation (L-ZSON) tasks, which takes in a freeform language description of an unseen target object and navigates to find out the target object in an inexperienced environment. In general, an L-ZSON agent should able to visually ground the target object by understanding the freeform language description of it and recognizing the corresponding visual object in camera images. Moreover, the L-ZSON agent should be also able to build a rich spatial context map over the unknown environment and decide efficient exploration actions based on the map until the target object is present in the field of view. To address these challenging issues, we proposes AML (Agent Model for L-ZSON), a novel L-ZSON agent model to make effective use of AI foundation models such as Large Language Model (LLM) and Vision-Language model (VLM). In order to tackle the visual grounding issue of the target object description, our agent model employs GLEE, a VLM pretrained for locating and identifying arbitrary objects in images and videos in the open world scenario. To meet the exploration policy issue, the proposed agent model leverages the commonsense knowledge of LLM to make sequential navigational decisions. By conducting various quantitative and qualitative experiments with RoboTHOR, the 3D simulation platform and PASTURE, the L-ZSON benchmark dataset, we show the superior performance of the proposed agent model.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.1
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• pp.8-15
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• 2007

Freeway corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. The design of experiment, neural network, and simulated annealing are used for optimization.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12C
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• pp.225-232
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• 2001

In this paper, we describe a mechanism that supports the mobility service for VPN(Virtual Private Network) users on MPLS(Multiprotocol Label Switching) network. The MPLS VPN considered in this study is controlled by CE(Customer Edge) routers. In such a VPN, CE routers have additional functions to support mobile VPN users, i.e., Home Agent function, foreign Agent function, Correspondent Agent function. This mechanism is applied when a VPN node moves to other site of the saute VPN, or when it moves to other site of a different VPN, or to a non-VPN site. We perform a simulation study to compare the performance of CE based MPLS VPN with that of PE(Provider Edge) based MPLS VPN with mobility support.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.6
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• pp.353-362
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• 2015

In order to provide smart devices with high quality multimedia streaming services, an adaptive streaming technique over HTTP has been received much attention recently and the Dynamic Adaptive Streaming over HTTP (DASH) standard has been established. In DASH, however, the technique to select an appropriate quality of multimedia based on the performance metrics measured in a smart device might have some difficulties to reflect the capabilities of other neighboring smart devices and dynamic network conditions in real time. To solve the problem, this paper proposes a novel software agent approach, called DASH agent (DA), which gathers and analyzes the device capabilities and dynamic network conditions in real time and finally determines the highest achievable quality of segment to meet the best Quality of Experience (QoE) in current situations. The simulation results show that our approach provides higher quality of multimedia segments with less frequency of quality changes to lower quality of multimedia segments.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.337-345
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• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

• Journal of Korea Game Society
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• v.19 no.3
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• pp.5-14
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• 2019

The gaming server is based on a distributed server. In order to distribute workloads of gaming servers, distributed gaming servers apply some algorithms which divide each of gaming server's workload into balanced workload among the gaming servers and as a result, efficiently manage response time and fusibility of server requested by the clients. In this paper, we propose a load balancing agent using PPO(Proximal Policy Optimization) which is one of the methods from a greedy algorithm and Policy Gradient which is from Reinforcement Learning. The proposed load balancing agent is compared with the previous researches based on the simulation.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.