• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.25.2-25
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• 2001

This paper describes a mobile robot intended for being employed in a multi-agent system. We have already proposed a multi-agent system which realizes patient-aid by helping a lying patient take a distant object on the table. In this paper, a mobile robot agent is developed and is included in the system. An effective man-machine communication strategy is proposed by use of a vision agent settled on the ceiling. If a human (assumed to be a patient) wishes to take an object distant on the floor, he points to the object. The vision agent detects the direction of his arm by image processing and guesses which object he intends to take. The vision agent asks him if it is what he wants and, if yes, the mobile robot runs to take and bring it to him. The system is overviewed with the explanation of a mobile robot. Some experimental results are shown with discussion.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.507-512
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• 1998

It is an interesting area in the field of artificial intelligence to and an analytic model of cooperative structure for multi-agent 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 co-operative behavior: A modified genetic algorithm was applied to automating the discovery of a fuzzy logic controller jot multi-agents playing a pursuit game. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to and the fuzzy logic controller seems to be promising.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.457-467
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• 2004

In this paper, a robot is considered as an agent, a structure of robot is presented which consisted by multi-subagents and they have diverse capacity such as perception, intelligence, action etc., required for robot. Also, subagents are consisted by micro-agent($\mu$agent) charged for elementary action required. The structure of robot control have two sub-agents, the one is behavior based reactive controller and action selection sub agent, and action selection sub-agent select a action based on the high label action and high performance, and which have a learning mechanism based on the reinforcement learning. For presented robot structure, it is easy to give intelligence to each element of action and a new approach of multi robot control. Presented robot is simulated for two goals: chaotic exploration and obstacle avoidance, and fabricated by using 8bit microcontroller, and experimented.

• 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.

• Journal of Power Electronics
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• v.15 no.2
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• pp.455-468
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• 2015

A microgrid (MG) with integrated renewable energy resources can benefit both utility companies and customers. As a result, they are attracting a great deal of attention. The control of a MG is very important for the stable operation of a MG. The droop-control method is popular since it avoids circulating currents among the converters without using any critical communication between them. Traditional droop control methods have the drawback of an inherent trade-off between power sharing and voltage and frequency regulation. An adaptive droop control method is proposed, which can operate in both the island mode and the grid-connected mode. It can also ensure smooth switching between these two modes. Furthermore, the voltage and frequency of a MG can be restored by using the proposed droop controller. Meanwhile, the active power can be dispatched appropriately in both operating modes based on the capacity or running cost of the Distributed Generators (DGs). The global information (such as the average voltage and output active power of the MG and so on) required by the proposed droop control method to restore the voltage and frequency deviations can be acquired distributedly based on the Multi Agent System (MAS). Simulation studies in PSCAD demonstrate the effectiveness of the proposed control method.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.249-256
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• 2003

The most important problems in the multi-agent system are to accomplish a goal through the efficient coordination of several agents and to prevent collision with other agents. In this paper, we propose a new control strategy for succeeding the goal of the prey pursuit problem efficiently. Our control method uses reinforcement learning to control the multi-agent system and consider the distance as well as the space relationship between the agents in the state space of the prey pursuit problem.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1650-1657
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• 2017

In this study, the distributed secondary voltage control of islanded microgrids with multi-agent consensus algorithm is investigated. As an alternative to a time-triggered approach, an event-triggered scheme is proposed to reduce the communication load among inverter-based distributed generators (DGs). The proposed aperiodic control scheme reduced unnecessary utilization of limited network bandwidth without degrading control performance. By properly establishing a distributed triggering condition in DG local controller, each inverter is only required to send voltage information when its own event occurs. The compensation of voltage amplitude deviation can be realized, and redundant data exchange related to fixed high sampling rate can be avoided. Therefore, an efficient use of communication infrastructure can be realized, particularly when the system is operating in steady state. The effectiveness of the proposed scheme is verified by simulations on a microgrid test system.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.292-297
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• 1999

Evolving in artificial agent is an extremely difficult problem, but on the other hand, a challenging task. At present the studies mainly centered on single agent learning problem. In our case, we use simulated soccer to investigate multi-agent cooperative learning. Consider the fundamental differences in learning mechanism, existing reinforcement learning algorithms can be roughly classified into two types-that based on evaluation functions and that of searching policy space directly. Genetic Programming developed from Genetic Algorithms is one of the most well known approaches belonging to the latter. In this paper, we give detailed algorithm description as well as data construction that are necessary for learning single agent strategies at first. In following step moreover, we will extend developed methods into multiple robot domains. game. We investigate and contrast two different methods-simple team learning and sub-group loaming and conclude the paper with some experimental results.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.27-30
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• 2002

Recently, there are lots of concerning on the control of multi-agent control system and mixed reality integrating real and virtual environments. In this paper, an integrated agent control system based on mixed reality and mobile environment is proposed. The system consists of a manager, agents, a mapping module, a geographic information module, a WAP server, and a mobile manager. The manager has Hybrid Device Manager(HDM) working for revising images and position data of the agents to display that at the 3D virtual and mobile environments respectively. Especially, the images of the agent is translated to LBM format and displayed on the mobile phone, and the current position of the agent is displayed on the display screen, so that a user are able to control the agent when he is moving. Experimental results shows the proposed system lets us control the agents conveniently at a computer and a mobile phone.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.584-590
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• 2000

Urban traffic situations are extremely complex and highly interactive. The multi-agent systems approach can provide a new desirable solution. Currently, a traffic simulator is needed to understand and explore the difficulties in an agent-oriented traffic control. This paper presents an agent-oriented fuzzy logic controller for multiple crossroads simulation. A fuzzy logic control simulation with variables of arrival, queue, and traffic volume could alleviate traffic congestion. We developed an agent-oriented simulator suitable for traffic junctions with η$\times$η intersections in Visual C++. The proposed method adaptively controls the cycle of traffic signals even though the traffic volume varies. The effectiveness of this method was shown through simulation of multiple intersections.