In the manufacturing industry, dispatching systems play a crucial role in enhancing production efficiency and optimizing production volume. However, in dynamic production environments, conventional static dispatching methods struggle to adapt to various environmental conditions and constraints, leading to problems such as reduced production volume, delays, and resource wastage. Therefore, there is a need for dynamic dispatching methods that can quickly adapt to changes in the environment. In this study, we aim to develop an agent-based model that considers dynamic situations through interaction between agents. Additionally, we intend to utilize the Q-learning algorithm, which possesses the characteristics of temporal difference (TD) learning, to automatically update and adapt to dynamic situations. This means that Q-learning can effectively consider dynamic environments by sensitively responding to changes in the state space and selecting optimal dispatching rules accordingly. The state space includes information such as inventory and work-in-process levels, order fulfilment status, and machine status, which are used to select the optimal dispatching rules. Furthermore, we aim to minimize total tardiness and the number of setup changes using reinforcement learning. Finally, we will develop a dynamic dispatching system using Q-learning and compare its performance with conventional static dispatching methods.

Compound logistics is a service aimed to enhance logistics efficiency by supporting that shippers and consigners jointly use logistics facilities. Many of these services have taken place both domestically and internationally, but the joint logistics services for e-commerce have not been spread yet, since the number of the parcels that the consigners transact business is usually small. As one of meaningful ways to improve utilization of compound logistics, we propose a brokerage service for shipper and consigners based on the hybrid recommendation system using very well-known classification and clustering methods. The existing recommendation system has drawn a relatively low satisfaction as it brought about one-to-one matches between consignors and logistics vendors in that such matching constrains choice range of the users to one-to-one matching each other. However, the implemented hybrid recommendation system based brokerage agent service system can provide multiple choice options to mutual users with descending ranks, which is a result of the recommendation considering transaction preferences of the users. In addition, we applied feature selection methods in order to avoid inducing a meaningless large size recommendation model and reduce a simple model. Finally, we implemented the hybrid recommendation system based brokerage agent service system that shippers and consigners can join, which is the system having capability previously described functions such as feature selection and recommendation. As a result, it turns out that the proposed hybrid recommendation based brokerage service system showed the enhanced efficiency with respect to logistics management, compared to the existing one by reporting two round simulation results.

  In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. T

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.

Recently, robotic automation in clinical laboratory becomes of keen interest as a fusion of bio and robotic technology. In this paper, we present a new robotic platform for clinical tests suitable for small or medium sized laboratories using mobile robots. The mobile robot called Mobile Agent is designed as transfer system of blood samples, reagents, microplates, and any instruments. Also, the developed mobile agent can perform diverse tests simultaneously based on its cooperative and distributed ability. The driving circuits for the mobile agent are embedded in the robot, and each mobile agent communicates with other agents by using Bluetooth communication. The RFID system is used to recognize patient information. Also, the magnetic hall sensor is embedded to remove and compensate the cumulated error of locomotion at the bottom of mobile agent. The proposed mobile agent can be easily used for various applications because it is designed to be compatible with general software development tools. The Mobile agents are manufactured, and feasibility of the robot and localization of the agents using magnetic hall sensor are validated by preliminary experiments.

세계무역기구(WTO : World Trade Organization)를 설립된 이후 무역은 세계화가 되고, WTO에서 무역 장벽을 낮춰 국가 간의 경제 교류가 점점 증가하면서 국제적인 물류 시스템이 필요하게 되었다. 원가를 절감하기 위해 대랑 수송 수판으로 컨테이너선을 이용하면서 대형 컨테이너 선사들은 국제적인 물류 시스템의 대안으로 기업에게 화물추적 정보시스템의 제공이나 장비, 기기 관리를 위한 정보시스템 네트워크를 구축하여 자동화 시스템을 도입했다. 컨테이너 터미널 자동화를 위해 본 논문에서는 수시로 변경되는 정보를 인식하여 에이전트간의 정보교환을 위해 유동적으로 대처할 수 있는 XML(eXtensive Markup Language)과 JMS(Java Message Service)를 이용한 멀티에이전트간의 통신모델을 제안했다. 이 논문은 기존의 자동화한 컨테이너 터미널 시스템 사례와 자동화 시스템을 개발하는데 어려움, 컨테이너 터미널 시스템이 요구하는 통신과 자동화에 대하여 분석하였다.