• Restorative Dentistry and Endodontics
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• v.20 no.2
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• pp.732-743
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• 1995

The purpose of this study was to evaluate the adaptation of light cured dentin bonding agents to tooth structure by measuring contraction gaps on interfaces between cavity wall and composite resin under SEM study. In this study, class V cavities with cementum margin were prepared on the buccal surfaces of 15 extracted human premolar teeth and teeth were randomly assigned 3 groups of 5 teeth each. The cavities were filled with three dentin bonding agents and two composite resins were investigated for this study: three dentin bonding agents; Scotchbond 2, Scotchbond Multi-Purpose. All-Bond 2, two composite resins; Silux Pius, Z-100. Group 1 : Scotchbond 2 + Silux Plus Group 2 : Scotchbond Multi~Purpose + Z-100 Group 3 : All-Bond 2 + Z-100 The restored teeth were stored in 100% relative humidity at $37^{\circ}C$ for 7 days. And then, the roots of the teeth were removed with the tapered fissure bur and the remaining crowns were sectioned occlusogingivally through the center of restorations. Adaptation at tooth-restoration interface was assesed occlusally, gingivally, and axially by scanning electron microscope. The results were as follows : 1. In Group 1, the adaptation to dentinal wall of Scotchbond 2 was poor, but the adaptation to enamel wall of Scotchbond 2 was excellent. 2. In Group 2, the adaptation to occlusal was axial wall and gingival wall of Scotchbond Multi-Purpose was excellent. Especially in axially wall, the dentin bonding agents infiltrated into dentinal tubules and there was excellent adaptation to dentinal wall. 3. In Group 3, the adaptation to occlusal wall and axial wall of All-Bond 2 was excellent. But in gingival wall, there was gap formation between composite resin and dentin bonding agent.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.1
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• pp.19-28
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• 2012

We consider a multi-agent scheduling problem such that each agent tries to maximize the weighted number of just-in-time jobs. Two objectives are considered : the first is to find the optimal solution for one agent with constraints on the other agents' weight functions, and the second is to find the largest set of efficient schedules of which corresponding objective vectors are different for the case with identical weights. We show that when the number of agents is fixed, the single machine case with the first objective is NP-hard in the ordinary sense, and present the polynomial- time algorithm for the two-machine flow shop case with the second objective and identical weights.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.333-342
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• 2004

This paper presents a framework for the self-organization of swarm systems based on coupled nonlinear oscillators (CNOs). In this scheme, multiple agents in a swarm self-organize to flock and arrange themselves as a group using CNOs, which are able to keep a certain distance by the attractive and repulsive forces among different agents. A theoretical approach of flocking behavior by CNOs and a design guideline of CNO parameters are proposed. Finally, the formation scenario for cooperative multi-agent groups is investigated to demonstrate group behaviors such as aggregation, migration, homing and so on. The task for each group in this scenario is to perform a series of processes such as gathering into a whole group or splitting into two groups, and then to return to the base while avoiding collision with agents in different groups and maintaining the formation of each group.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.1-20
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• 2009

Negotiation is a process of reaching an agreement on the terms of a transaction. such as price, quantity, for two or more parties. Negotiation tries to maximize the benefits for all parties concerned. instead of using human-based negotiation. the e-commerce environment provides such an environment as adopting automated negotiation. Thus. choosing agent technology is appropriate for an automatic electronic negotiation platform. since autonomous software agents strive for the best deal on behalf of the human participants. Negotiation agents need a clear-cut definition of negotiation models or strategies. In reality, most bargaining systems embody nearly one negotiation model. In this article. we present a mobile agent negotiation system with reusable negotiation strategies that allows agents to dynamically embody a user's favorite negotiation strategy which can be preinstalled as a component in the system. We develop a prototype system, which is fully implemented in compliance with FIPA specifications, and then. describe the benefits of using the system.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.218-223
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• 2012

Maintenance and improvement of the graph connectivity is very important for decentralized multi-agent systems. Although the CBBA (Consensus-Based Bundle Algorithm) guarantees suboptimal performance and bounded convergence time, it is only valid for connected graphs. In this study, we apply a decentralized estimation procedure that allows each agent to track the algebraic connectivity of a time-varying graph. Based on this estimation, we design a decentralized gradient controller to maintain the graph connectivity while agents are traveling to perform assigned tasks. Simulation result for fully-actuated first-order agents that move in a 2-D plane are presented.

• 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.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.21-26
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• 2003

Negotiation plays a fundamental role in human cooperative activities, allowing people to resolve conflicts that could interfere with cooperative behaviors. Negotiation In multi-agent systems is achieved through the exchange of messages In a shared agent communication language (ACL). We introduce a rational negotiation meta-language for autonomous, self-interested, and resource-bounded artificial BDI agents. We then propose a negotiation protocol for BDI agents with communicative acts based on their mental states.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.353-363
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• 2008

A multi-agent system has a longer learning period and larger state-spaces than a sin91e agent system. In this paper, we suggest a new method to reduce the learning time of Nash Q-learning in a multi-agent environment. We apply Macro-actions to Nash Q-learning to improve the teaming speed. In the Nash Q-teaming scheme, when agents select actions, rewards are accumulated like Macro-actions. In the experiments, we compare Nash Q-learning using Macro-actions with general Nash Q-learning. First, we observed how many times the agents achieve their goals. The results of this experiment show that agents using Nash Q-learning and 4 Macro-actions have 9.46% better performance than Nash Q-learning using only 4 primitive actions. Second, when agents use Macro-actions, Q-values are accumulated 2.6 times more. Finally, agents using Macro-actions select less actions about 44%. As a result, agents select fewer actions and Macro-actions improve the Q-value's update. It the agents' learning speeds improve.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1124-1128
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• 2005

In this paper, a plan-coordination architecture is proposed for multi-agent control in the fractal manufacturing system (FrMS). A fractal in FrMS is a set of distributed agents whose goal can be achieved through cooperation, coordination, and negotiation with other agents. Since each agent in the FrMS generates, achieves, and modifies its own plan fragments autonomously during the coordination process with other agents, it is necessary to develop a systematic methodology for the achievement of global plan in the manufacturing system. The heterarchical structure of the FrMS provides a compromised plan-coordination approach, it compromise a centralized plan-generation/execution (which mainly focuses on the maximization of throughput) with a distributed one (which focuses on the autonomy of each module and flexibility of the whole system). Plan-coordinators in lower level fractal independently generate plan fragments according to the global plan of higher level fractal, and plan-coordinators in higher level fractal mediate/coordinate the plan fragments to enhance the global performance of the system. This paper assumes that generation method of the plan fragments and the negotiation policy of the fractal is achieved by a simple process, and we mainly focuses on the information exchanging and distributed decision making process to coordinate the combinations of plan fragments within a limited exchange of information.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.66-71
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• 2007

To adapt environment changing high speed and improve rapidly response ability for variation of environment and reduce delay time of decision making inlet agents, the derivation of user's preference and alternative are required. In this paper, we propose an efficient coordination method of multi-agents based on fuzzy decision making with the solution proposed by agents in the view of Pareto optimality. Our method generates the optimal alternative by using weighted value. We compute importance of attributes of winner agent, then can obtain the priorities lot attributes. The result of our method is analyzed that of Yager's method.