• Title/Summary/Keyword: 에이전트 기반 모델

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Knowledge Representation and Reasoning using Metalogic in a Cooperative Multiagent Environment

  • Kim, Koono
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.7
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    • pp.35-48
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    • 2022
  • In this study, it propose a proof theory method for expressing and reasoning knowledge in a multiagent environment. Since this method determines logical results in a mechanical way, it has developed as a core field from early AI research. However, since the proposition cannot always be proved in any set of closed sentences, in order for the logical result to be determinable, the range of expression is limited to the sentence in the form of a clause. In addition, the resolution principle, a simple and strong reasoning rule applicable only to clause-type sentences, is applied. Also, since the proof theory can be expressed as a meta predicate, it can be extended to the metalogic of the proof theory. Metalogic can be superior in terms of practicality and efficiency based on improved expressive power over epistemic logic of model theory. To prove this, the semantic method of epistemic logic and the metalogic method of proof theory are applied to the Muddy Children problem, respectively. As a result, it prove that the method of expressing and reasoning knowledge and common knowledge using metalogic in a cooperative multiagent environment is more efficient.

Development of Agent-based Platform for Coordinated Scheduling in Global Supply Chain (글로벌 공급사슬에서 경쟁협력 스케줄링을 위한 에이전트 기반 플랫폼 구축)

  • Lee, Jung-Seung;Choi, Seong-Woo
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.213-226
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    • 2011
  • In global supply chain, the scheduling problems of large products such as ships, airplanes, space shuttles, assembled constructions, and/or automobiles are complicated by nature. New scheduling systems are often developed in order to reduce inherent computational complexity. As a result, a problem can be decomposed into small sub-problems, problems that contain independently small scheduling systems integrating into the initial problem. As one of the authors experienced, DAS (Daewoo Shipbuilding Scheduling System) has adopted a two-layered hierarchical architecture. In the hierarchical architecture, individual scheduling systems composed of a high-level dock scheduler, DAS-ERECT and low-level assembly plant schedulers, DAS-PBS, DAS-3DS, DAS-NPS, and DAS-A7 try to search the best schedules under their own constraints. Moreover, the steep growth of communication technology and logistics enables it to introduce distributed multi-nation production plants by which different parts are produced by designated plants. Therefore vertical and lateral coordination among decomposed scheduling systems is necessary. No standard coordination mechanism of multiple scheduling systems exists, even though there are various scheduling systems existing in the area of scheduling research. Previous research regarding the coordination mechanism has mainly focused on external conversation without capacity model. Prior research has heavily focuses on agent-based coordination in the area of agent research. Yet, no scheduling domain has been developed. Previous research regarding the agent-based scheduling has paid its ample attention to internal coordination of scheduling process, a process that has not been efficient. In this study, we suggest a general framework for agent-based coordination of multiple scheduling systems in global supply chain. The purpose of this study was to design a standard coordination mechanism. To do so, we first define an individual scheduling agent responsible for their own plants and a meta-level coordination agent involved with each individual scheduling agent. We then suggest variables and values describing the individual scheduling agent and meta-level coordination agent. These variables and values are represented by Backus-Naur Form. Second, we suggest scheduling agent communication protocols for each scheduling agent topology classified into the system architectures, existence or nonexistence of coordinator, and directions of coordination. If there was a coordinating agent, an individual scheduling agent could communicate with another individual agent indirectly through the coordinator. On the other hand, if there was not any coordinating agent existing, an individual scheduling agent should communicate with another individual agent directly. To apply agent communication language specifically to the scheduling coordination domain, we had to additionally define an inner language, a language that suitably expresses scheduling coordination. A scheduling agent communication language is devised for the communication among agents independent of domain. We adopt three message layers which are ACL layer, scheduling coordination layer, and industry-specific layer. The ACL layer is a domain independent outer language layer. The scheduling coordination layer has terms necessary for scheduling coordination. The industry-specific layer expresses the industry specification. Third, in order to improve the efficiency of communication among scheduling agents and avoid possible infinite loops, we suggest a look-ahead load balancing model which supports to monitor participating agents and to analyze the status of the agents. To build the look-ahead load balancing model, the status of participating agents should be monitored. Most of all, the amount of sharing information should be considered. If complete information is collected, updating and maintenance cost of sharing information will be increasing although the frequency of communication will be decreasing. Therefore the level of detail and updating period of sharing information should be decided contingently. By means of this standard coordination mechanism, we can easily model coordination processes of multiple scheduling systems into supply chain. Finally, we apply this mechanism to shipbuilding domain and develop a prototype system which consists of a dock-scheduling agent, four assembly- plant-scheduling agents, and a meta-level coordination agent. A series of experiments using the real world data are used to empirically examine this mechanism. The results of this study show that the effect of agent-based platform on coordinated scheduling is evident in terms of the number of tardy jobs, tardiness, and makespan.

A Study on the Performance Evaluation of G2B Procurement Process Innovation by Using MAS: Korea G2B KONEPS Case (멀티에이전트시스템(MAS)을 이용한 G2B 조달 프로세스 혁신의 효과평가에 관한 연구 : 나라장터 G2B사례)

  • Seo, Won-Jun;Lee, Dae-Cheor;Lim, Gyoo-Gun
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.157-175
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    • 2012
  • It is difficult to evaluate the performance of process innovation of e-procurement which has large scale and complex processes. The existing evaluation methods for measuring the effects of process innovation have been mainly done with statistically quantitative methods by analyzing operational data or with qualitative methods by conducting surveys and interviews. However, these methods have some limitations to evaluate the effects because the performance evaluation of e-procurement process innovation should consider the interactions among participants who are active either directly or indirectly through the processes. This study considers the e-procurement process as a complex system and develops a simulation model based on MAS(Multi-Agent System) to evaluate the effects of e-procurement process innovation. Multi-agent based simulation allows observing interaction patterns of objects in virtual world through relationship among objects and their behavioral mechanism. Agent-based simulation is suitable especially for complex business problems. In this study, we used Netlogo Version 4.1.3 as a MAS simulation tool which was developed in Northwestern University. To do this, we developed a interaction model of agents in MAS environment. We defined process agents and task agents, and assigned their behavioral characteristics. The developed simulation model was applied to G2B system (KONEPS: Korea ON-line E-Procurement System) of Public Procurement Service (PPS) in Korea and used to evaluate the innovation effects of the G2B system. KONEPS is a successfully established e-procurement system started in the year 2002. KONEPS is a representative e-Procurement system which integrates characteristics of e-commerce into government for business procurement activities. KONEPS deserves the international recognition considering the annual transaction volume of 56 billion dollars, daily exchanges of electronic documents, users consisted of 121,000 suppliers and 37,000 public organizations, and the 4.5 billion dollars of cost saving. For the simulation, we analyzed the e-procurement of process of KONEPS into eight sub processes such as 'process 1: search products and acquisition of proposal', 'process 2 : review the methods of contracts and item features', 'process 3 : a notice of bid', 'process 4 : registration and confirmation of qualification', 'process 5 : bidding', 'process 6 : a screening test', 'process 7 : contracts', and 'process 8 : invoice and payment'. For the parameter settings of the agents behavior, we collected some data from the transactional database of PPS and some information by conducting a survey. The used data for the simulation are 'participants (government organizations, local government organizations and public institutions)', 'the number of bidding per year', 'the number of total contracts', 'the number of shopping mall transactions', 'the rate of contracts between bidding and shopping mall', 'the successful bidding ratio', and the estimated time for each process. The comparison was done for the difference of time consumption between 'before the innovation (As-was)' and 'after the innovation (As-is).' The results showed that there were productivity improvements in every eight sub processes. The decrease ratio of 'average number of task processing' was 92.7% and the decrease ratio of 'average time of task processing' was 95.4% in entire processes when we use G2B system comparing to the conventional method. Also, this study found that the process innovation effect will be enhanced if the task process related to the 'contract' can be improved. This study shows the usability and possibility of using MAS in process innovation evaluation and its modeling.

Modeling and Simulation on One-vs-One Air Combat with Deep Reinforcement Learning (깊은강화학습 기반 1-vs-1 공중전 모델링 및 시뮬레이션)

  • Moon, Il-Chul;Jung, Minjae;Kim, Dongjun
    • Journal of the Korea Society for Simulation
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    • v.29 no.1
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    • pp.39-46
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    • 2020
  • The utilization of artificial intelligence (AI) in the engagement has been a key research topic in the defense field during the last decade. To pursue this utilization, it is imperative to acquire a realistic simulation to train an AI engagement agent with a synthetic, but realistic field. This paper is a case study of training an AI agent to operate with a hardware realism in the air-warfare dog-fighting. Particularly, this paper models the pursuit of an opponent in the dog-fighting setting with a gun-only engagement. In this context, the AI agent requires to make a decision on the pursuit style and intensity. We developed a realistic hardware simulator and trained the agent with a reinforcement learning. Our training shows a success resulting in a lead pursuit with a decreased engagement time and a high reward.

Multi-Agent based Operation System Modeling for Automated Container Terminals (자동화 컨테이너 터미널을 위한 멀티에이전트 기반의 운영시스템 모델링)

  • Kang K W.;Yu S. Y.;Mo S. J.;Yim J. H.
    • Journal of Navigation and Port Research
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    • v.29 no.6 s.102
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    • pp.567-572
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    • 2005
  • Trade between nations has been globalized since establishing the WTO(World Trade Organization). By lowering trading barriers under the WTO's system, trade in goods has been gradually increased It requires global logistic system that transports goods in between nations. To save cost of product, cargo of product is containerized and container ships to carry container cargo is going to be bigger: In the market, there are many vendors to provide artificial intelligent modules to operate container terminal. In order to integrate automated container terminal system easily and successfully, this thesis proposes high-level XML/ JMS( eXtensive Markup Language/Java Message Service) communication model and multi-agent based system architecture to share knowledges, solve problems, and active objectives by cooperating between autonomous and intelligent agents that are developed by 3rd party companies in the market. This thesis analyzed current situation of advanced automated container terminal with case studies on implemented systems and difficulties to develop automated container terminal system, reviewed technologies of intelligent agent, communication and automation that unmaned automated container terminal is required.

Optimal Supply Chain formation using Agent Negotiation in SET Model based Make-To-Order (최적 공급사슬 구성을 위한 에이전트 협상방법론 개발)

  • Kim Hyun-Soo;Cho Jae-Hyung;Choi Hyung-Rim;Hong Soon-Goo
    • Journal of Intelligence and Information Systems
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    • v.12 no.2
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    • pp.99-123
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    • 2006
  • In an effect to composite an optimal supply chain, this study has introduced an agent-based negotiation as a method to assign a lot of orders to a large number of participants. As a resources allocation mechanism to form a strategic cooperation based on information sharing between supply chain members(buyers, manufacturers, suppliers), this agent negotiation provides coordination functions allowing all participants to make a profit and accomplishing Pareto optimum solution from the viewpoint of a whole supply chain. A SET model-based scheduling takes into consideration both earliness production cost and tardiness production cost, along with a competitive relationship between multiple participants. This study has tried to prove that the result of an agent-based negotiation is a Pareto optimal solution under the dynamic supply chain environment, establishing the mathematical formulation for a performance test, and making a comparison with the heuristic Branch & Bound method.

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A Development of a Framework for Building Knowledge based Augmented Reality System (지식기반 증강현실 시스템 구축을 위한 프레임워크 개발)

  • Woo, Chong-Woo;Lee, Doo-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.7
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    • pp.49-58
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    • 2011
  • Augmented Reality(AR) assists human's cognitive ability through the information visualization by substantiating information about virtual situation. This technology is studied in a variety of ways including education, design, industry, and so on, by various supply of information devices equipped with cameras and display monitors. Since the most of the AR system depends on limited interaction that responds to the order from user, it can not reflect diverse real world situation. In this study, we suggest a knowledge based augmented reality system, which is composed of context awareness agent that provides recognized context information, along with knowledge based component that provides intelligent capability by utilizing domain knowledges. With this capability, the augmented object can generate dynamic model intelligently by reflecting context information, and can make the interaction possible among the multiple objects. We developed rule based context awareness system along with 3D model generation, and tested interaction among the augmented objects. And we suggest a framework that can provide a convenient way of developing augmented reality system for user.

Analysis of the Ecological Impact of Climate Change using ABMS: A Case Study of Polar Bears and Glacier (기후 변화의 생태계 영향에 대한 ABMS 연구 -빙하감소와 북극곰의 모의실험을 바탕으로-)

  • Cho, Sung-Jin;Na, Yu-Gyung;Lee, Joon-Young;Joh, Chang-Hyeon
    • Journal of the Korean Geographical Society
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    • v.46 no.3
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    • pp.291-303
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    • 2011
  • It has actively advanced to study the impact of climate change on ecosystem. This study addresses ABMS (Agent Based Modeling and Simulation) as a methodology of ecosystem research. ABMS would suggest the possibility of practical use in this sector. This study would investigate how the melting speed of glacier in the arctic influences the extinction period of polar bears. The Polar Bears and Glacier Model in this study is expected to contribute to accurate prediction of the polar bear's extinction period. The suggested ABMS could also be applied to the study of various factors of ecosystem in general.

A Design and Implementation of The Deep Learning-Based Senior Care Service Application Using AI Speaker

  • Mun Seop Yun;Sang Hyuk Yoon;Ki Won Lee;Se Hoon Kim;Min Woo Lee;Ho-Young Kwak;Won Joo Lee
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.4
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    • pp.23-30
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    • 2024
  • In this paper, we propose a deep learning-based personalized senior care service application. The proposed application uses Speech to Text technology to convert the user's speech into text and uses it as input to Autogen, an interactive multi-agent large-scale language model developed by Microsoft, for user convenience. Autogen uses data from previous conversations between the senior and ChatBot to understand the other user's intent and respond to the response, and then uses a back-end agent to create a wish list, a shared calendar, and a greeting message with the other user's voice through a deep learning model for voice cloning. Additionally, the application can perform home IoT services with SKT's AI speaker (NUGU). The proposed application is expected to contribute to future AI-based senior care technology.

A Bio-Inspired Modeling of Visual Information Processing for Action Recognition (생체 기반 시각정보처리 동작인식 모델링)

  • Kim, JinOk
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.8
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    • pp.299-308
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    • 2014
  • Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.