• Title/Summary/Keyword: Artificial Agent

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Comparison of Learning Performance by Reinforcement Learning Agent Visibility Information Difference (강화학습 에이전트 시야 정보 차이에 의한 학습 성능 비교)

  • Kim, Chan Sub;Jang, Si-Hwan;Yang, Seong-Il;Kang, Shin Jin
    • Journal of Korea Game Society
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    • v.21 no.5
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    • pp.17-28
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    • 2021
  • Reinforcement learning, in which artificial intelligence develops itself to find the best solution to problems, is a technology that is highly valuable in many fields. In particular, the game field has the advantage of providing a virtual environment for problem-solving to reinforcement learning artificial intelligence, and reinforcement learning agents solve problems about their environment by identifying information about their situation and environment using observations. In this experiment, the instant dungeon environment of the RPG game was simplified and produced and various observation variables related to the field of view were set to the agent. As a result of the experiment, it was possible to figure out how much each set variable affects the learning speed, and these results can be referred to in the study of game RPG reinforcement learning.

A Proposal for Software Framework of Intelligent Drones Performing Autonomous Missions (지능형 드론의 자율 임무 수행을 위한 소프트웨어 프레임워크 제안)

  • Shin, Ju-chul;Kim, Seong-woo;Baek, Gyong-hoon;Seo, Min-gi
    • Journal of Advanced Navigation Technology
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    • v.26 no.4
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    • pp.205-210
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    • 2022
  • Drones, which have rapidly grown along with the 4th industrial revolution, spread over industries and also widely used for military purposes. In recent wars in Europe, drones are being evaluated as a game changer on the battlefield, and their importance for military use is being highlighted. The Republic of Korea Army also planned drone-bot systems including various drones suitable for echelons and missions of the military as future defense forces. The keyword of these drone-bot systems is autonomy by artificial intelligence. In addition, common use of operating platforms is required for the rapid development of various types of drones. In this paper, we propose software framework that applies diverse artificial intelligence technologies such as multi-agent system, cognitive architecture and knowledge-based context reasoning for mission autonomy and common use of military drones.

Energy-efficient intrusion detection system for secure acoustic communication in under water sensor networks

  • N. Nithiyanandam;C. Mahesh;S.P. Raja;S. Jeyapriyanga;T. Selva Banu Priya
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.6
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    • pp.1706-1727
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    • 2023
  • Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

The Parallel ANN(Artificial Neural Network) Simulator using Mobile Agent (이동 에이전트를 이용한 병렬 인공신경망 시뮬레이터)

  • Cho, Yong-Man;Kang, Tae-Won
    • The KIPS Transactions:PartB
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    • v.13B no.6 s.109
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    • pp.615-624
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    • 2006
  • The objective of this paper is to implement parallel multi-layer ANN(Artificial Neural Network) simulator based on the mobile agent system which is executed in parallel in the virtual parallel distributed computing environment. The Multi-Layer Neural Network is classified by training session, training data layer, node, md weight in the parallelization-level. In this study, We have developed and evaluated the simulator with which it is feasible to parallel the ANN in the training session and training data parallelization because these have relatively few network traffic. In this results, we have verified that the performance of parallelization is high about 3.3 times in the training session and training data. The great significance of this paper is that the performance of ANN's execution on virtual parallel computer is similar to that of ANN's execution on existing super-computer. Therefore, we think that the virtual parallel computer can be considerably helpful in developing the neural network because it decreases the training time which needs extra-time.

Artificial Intelligence in Personalized ICT Learning

  • Volodymyrivna, Krasheninnik Iryna;Vitaliiivna, Chorna Alona;Leonidovych, Koniukhov Serhii;Ibrahimova, Liudmyla;Iryna, Serdiuk
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.159-166
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    • 2022
  • Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

Multi-Agent Systems: Effective Approach for Cancer Care Information Management

  • Mohammadzadeh, Niloofar;Safdari, Reza;Rahimi, Azin
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.12
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    • pp.7757-7759
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    • 2013
  • Physicians, in order to study the causes of cancer, detect cancer earlier, prevent or determine the effectiveness of treatment, and specify the reasons for the treatment ineffectiveness, need to access accurate, comprehensive, and timely cancer data. The cancer care environment has become more complex because of the need for coordination and communication among health care professionals with different skills in a variety of roles and the existence of large amounts of data with various formats. The goals of health care systems in such a complex environment are correct health data management, providing appropriate information needs of users to enhance the integrity and quality of health care, timely access to accurate information and reducing medical errors. These roles in new systems with use of agents efficiently perform well. Because of the potential capability of agent systems to solve complex and dynamic health problems, health care system, in order to gain full advantage of E- health, steps must be taken to make use of this technology. Multi-agent systems have effective roles in health service quality improvement especially in telemedicine, emergency situations and management of chronic diseases such as cancer. In the design and implementation of agent based systems, planning items such as information confidentiality and privacy, architecture, communication standards, ethical and legal aspects, identification opportunities and barriers should be considered. It should be noted that usage of agent systems only with a technical view is associated with many problems such as lack of user acceptance. The aim of this commentary is to survey applications, opportunities and barriers of this new artificial intelligence tool for cancer care information as an approach to improve cancer care management.

Development of a Conversational Help Agent Using Approximate Pattern Matching (근사 패턴매칭을 이용한 대화형 도우미 에이전트의 개발)

  • 김수영;조성배
    • Korean Journal of Cognitive Science
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    • v.13 no.4
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    • pp.1-8
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    • 2002
  • As Internet grows, many web sites have been built, therefore much information has been registered. Because the web sites have more information, it is more difficult that the user can find the information wanted. Therefore, to get information that user wants easily, the full-text engine may be embedded to the web site. This paper is about developing the help conversational agent for a user to find the information that he wants through conversation with agent. The proposed method is based on the pattern matching of artificial intelligence, not natural language processing. If a user inputs any sentence, the help conversational agent responds to the sentence through preprocessing and pattern matching with knowledge. The knowledge is built with the XML format. With the approximate pattern matching, the agent picks up the appropriate response with some degree of similarities. At the experiment, some different sentences with the same meaning have been entered, then the agent recognized them as the same pattern, and it made a correct answer.

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Multi-agent System based on Blackboard System for Soccer Robot Implementation

  • Sanornoi, Nitiwat;Phurahong, Boonchana;Sooraksa, Pitikhate
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.2023-2028
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    • 2004
  • This paper reveals the utilization of the multi-gent system that based on the Blackboard system basis as the controller of Soccer Robot. This system is a portion of developing the Soccer Robot team for Robocup 2004 Competition. In this development, the intelligent control system was initiated by the combination of parallel and distributed blackboard structures with the principle design that generated from human body structures, which consists of the combination of two main systems, the organs system and the brain system. The system is designed using the control system theory based on Blackboard basis. Modification of the initial structures to corroborate the Soccer Robot and the structure's constituents are clarified accordingly. To demonstrate the idea, ITE-old team is given as a case study.

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GENETIC PROGRAMMING OF MULTI-AGENT COOPERATION STRATEGIES FOR TABLE TRANSPORT

  • Cho, Dong-Yeon;Zhang, Byoung-Tak
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.170-175
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    • 1998
  • Transporting a large table using multiple robotic agents requires at least two group behaviors of homing and herding which are to bo coordinated in a proper sequence. Existing GP methods for multi-agent learning are not practical enough to find an optimal solution in this domain. To evolve this kind of complex cooperative behavior we use a novel method called fitness switching. This method maintains a pool of basis fitness functions each of which corresponds to a primitive group behavior. The basis functions are then progressively combined into more complex fitness functions to co-evolve more complex behavior. The performance of the presented method is compared with that of two conventional methods. Experimental results show that coevolutionary fitness switching provides an effective mechanism for evolving complex emergent behavior which may not be solved by simple genetic programming.

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A study on agent shopping mall using Case-Based Reasoning (사례기반 추론을 이용한 에이젼트 쇼핑몰에 관한 연구)

  • 김영권
    • Journal of the Korea Computer Industry Society
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    • v.4 no.12
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    • pp.919-936
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    • 2003
  • Nowadays Electronic Commerce shopping mall is welcomed more and more on the Internet. It is expected that Shopping mall systems come to be various and adaptable to complex requirements according to customers who have these various needs, but just show products list, instead. This thesis suggests various structures of shopping malls showing interface agent model using Case-Based Reasoning one of reasoning method of Artificial Intelligence instead of the method of prior EC shopping mall. 1 constructed case base by making index with shopping mall members and customers' private informations, and pursued difference from prior EC shopping malls by proposing to customers cases of other users' selection of products who have similar private informations with them.

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