• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.339-345
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• 2012

This research aims to formulate a mathematical model and develop an algorithm for solving a location problem in emergency medical service vehicle parking. To find an optimal parking location which has the least risk score or risk priority number calculated from severity, occurrence, detection, and distance from parking location for emergency patients, data were collected from Pratoom sub-district Disaster Prevention and Mitigation Center from October 2010 to April 2011. The criteria of risk evaluation were modified from Automotive Industry Action Group's criteria. An adaptive simulated annealing algorithm with multiple cooling schedules called multi-agent simulated quenching (MASQ) is proposed for solving the problem in two schemes of algorithms including dual agent and triple agent quenching. The result showed that the solution obtained from both scheme of MASQ was better than the traditional solution. The best locations obtained from MASQ-dual agent quenching scheme was nodes #5 and #133. The risk score was reduced 61% from 6,022 to 2,371 points.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.445-454
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• 2000

의료 정보 시스템은 많은 지식과 의료 인력과의 연계가 필요하기 때문에, 멀티 에이전트 시스템의 활용 영역으로 적합하다. 본 논문에서는 지능형 의료 정보 제공을 위한 멀티 에이전트 시스템인 MAMI(Multi-Agent system for Medical Image)의 에이전트 플랫폼의 설계 및 구현 대해 기술한다. MAMI는 여러 의료 정보 중 의료 영상을 위한 멀티 에이전트 시스템이다. MAMI의 가장 중요한 구성 요소로서는 에이전트 플랫폼을 들 수 있다. 에이전트 플랫폼은 에이전트들이 동작할 수 있는 물리적 기반을 제공해 준다. MAMI는 FIPA(foundation for Intelligent Physical Agent)가 제안하는 관리 모델을 따르고 있다. MAMI에서는 COM(Common Object Model)과 XML(Extensible Markup Language)로 인코딩된 ACL(Agent Communication Language)을 메시지 교환에 이용하고 있다. 의료 영역의 특성상 의사와 같은 의료 전문 인력과의 연계는 반드시 필요하다. MAMI는 이를 위해서 의료 인력을 하나의 에이전트로 개념화하여 시스템에 연결한다. MAMI의 에이전트 플랫폼은 소프트웨어 에이전트와 휴먼 에이전트들이 지식을 공유하기에 적합한 물리적 기반을 제 공해주어 지능형 의료 정보 서비스를 용이하게 해준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.311-314
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• 2006

Our paper proposes an agent based automated negotiation model. The agents can perform an integrative negotiation with multi-issue in a one-to-many way. The negotiation protocol follows the offer-counteroffer principal, and an adapted offer generation strategy. With the utility theory, agent could evaluate the offers and determine the following actions. In order to yield a top-quality deal and shorten the negotiation period, agents propose multiple offers, which consist of a particular combination of issue values and lave the identical utility with the given utility. The experiment shows that the model ensures the participants could reach a better agreement in a short time.

• Korean Journal of Cognitive Science
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• v.10 no.1
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• pp.1-11
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• 1999

Agent-based systems technology has generated lots of excitement in these years because of its promise as a new paradigm for conceptualizing. designing. and l implementing software systems Especially, there has been many researches for multi agent system because of the characteristics that it fits to the distributed and open Internet environments. In a multiagent system. agents must cooperate with each other through a Coordination procedure. when the conflicts between agents arise. where those are caused b by the point that each action acts for a purpose separately without coordination. But P previous researches for coordination methods in multi agent system have a deficiency that they can not solve correctly the cooperation problem between agents which have different goals in dynamic environment. In this paper. we solve the cooperation problem of multiagent that has multiple goals in a dynamic environment. with an automatic cooperative coordination model using I reinforcement learning. We will show the two pursuit problems that we extend a traditional problem in multi agent systems area for modeling the restriction in the multiple goals in a dynamic environment. and we have verified the validity of the proposed model with an experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4379-4397
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• 2017

Three different improvements of the Velocity-based model were proposed in a minimal velocity-based pedestrian model. The improvements of the models are based on the different agent forms. The different representations of the agent lead to different results, in this paper, we simulated the pedestrian movements in some typical scenes by using different agent forms, and the agent forms included the circles with different radiuses, the ellipse and the multi-circle stand for one pedestrian. We have proposed a novel model of pedestrian dynamics to optimize the simulation. Our model specifies the pedestrian behavior using a dynamic ellipse, which is parameterized by their velocity and can improve the simulaton accuracy. We found a representation of the pedestrian much closer to the reality. The phenomena of the self-organization can be observable in the improved models.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.147-152
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• 1999

It is an interesting area in the field of artifical intelligence to find an analytic model of cooperative structure for multiagent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent agents solving a pursuit problem in a continuous world. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to find the fuzzy logic controller seems to be promising.

• Journal of the Korean Society of Safety
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• v.29 no.1
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• pp.59-63
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• 2014

Smoke is one of the most critical factor when escaping from the fire since it reduces visibility and interrupts finding emergency exit lights. Therefore, it is recommended that an evacuation simulation program should incorporate the smoke factor. In addition, it is suggested that the program should include not only the unilateral damage by the smoke but also the detour evacuation by risk communication. In this study, MAS (Multi Agent System)-based simulation program which incorporates the reduced walking speed by smoke and adopts the dispersion evacuation logic during escaping from the fire. To make comparison, a commercial evacuation program, Pathfinder was used. It was found that the simulation results of MAS (Multi Agent System)-based program is better than Pathfinder in terms of safe evacuation. It means that evacuation simulation need a additional evaluation categories that include not only quick evacuation time but also safe evacuee number.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.45-55
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• 2022

Recently, large-scale language models (LPLM) have been shown state-of-the-art performances in various tasks of natural language processing including intent classification. However, fine-tuning LPLM requires much computational cost for training and inference which is not appropriate for dialog system. In this paper, we propose compressed intent classification model for multi-agent in low-resource like CPU. Our method consists of two stages. First, we trained sentence encoder from LPLM then compressed it through knowledge distillation. Second, we trained agent-specific adapter for intent classification. The results of three intent classification datasets show that our method achieved 98% of the accuracy of LPLM with only 21% size of it.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.33-40
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• 2009

We study Interpreted Systems, ATL, and ATEL to capture the notion of time, knowledge, and strategy which are important in the analysis of multi-agent systems and propose strategic constraints based on subgame perfect Nash equilibrium of game theory as one of the solutions for the issues of ATEL which an agent can access the current state of the whole system when making up his strategy even when he should be uncertain about the state, and no explicit representation of actions in ATEL models makes some natural situations harder to model. Also, we present strategic constraints-based Interpreted Systems for model checking of multi-agent systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.133-138
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• 2013

This paper addresses a state consensus controller design technique of Takagi-Sugeno fuzzy model-based multi-agent systems in a continuous-time domain. We express the interconnection topology among the agents through graph theory. The design condition is represented in terms of linear matrix inequalities. Numerical example is provided to demonstrate the effectiveness of the proposed method.