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Journal articles on the topic 'Intelligent agents (computer software)'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Odhiambo, M. O., and P. O. Umenne. "NET-COMPUTER: Internet Computer Architecture and its Application in E-Commerce." Engineering, Technology & Applied Science Research 2, no. 6 (December 4, 2012): 302–9. http://dx.doi.org/10.48084/etasr.145.

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Research in Intelligent Agents has yielded interesting results, some of which have been translated into commercial ventures. Intelligent Agents are executable software components that represent the user, perform tasks on behalf of the user and when the task terminates, the Agents send the result to the user. Intelligent Agents are best suited for the Internet: a collection of computers connected together in a world-wide computer network. Swarm and HYDRA computer architectures for Agents’ execution were developed at the University of Surrey, UK in the 90s. The objective of the research was to

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Crawford, P. "Review: Intelligent Software Agents." Computer Bulletin 41, no. 3 (May 1, 1999): 31. http://dx.doi.org/10.1093/combul/41.3.31-c.

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Cross, Stuart R. "Agency, Contract and Intelligent Software Agents." International Review of Law, Computers & Technology 17, no. 2 (July 2003): 175–89. http://dx.doi.org/10.1080/1360086032000122556.

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SYCARA, KATIA, and DAJUN ZENG. "COORDINATION OF MULTIPLE INTELLIGENT SOFTWARE AGENTS." International Journal of Cooperative Information Systems 05, no. 02n03 (June 1996): 181–211. http://dx.doi.org/10.1142/s0218843096000087.

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We are investigating techniques for developing distributed and adaptive collections of information agents that coordinate to retrieve, filter and fuse information relevant to the user, task and situation, as well as anticipate user's information needs. In our system of agents, information gathering is seamlessly integrated with decision support. The task for which particular information is requested of the agents does not remain in the user's head but it is explicitly represented and supported through agent collaboration. In this paper we present the distributed system architecture, agent coll

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Wooldridge, Michael, and Nicholas R. Jennings. "Intelligent agents: theory and practice." Knowledge Engineering Review 10, no. 2 (June 1995): 115–52. http://dx.doi.org/10.1017/s0269888900008122.

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AbstractThe concept of anagenthas become important in both artificial intelligence (AT) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary).Agent theoryis concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the propertie

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Vinita, Kumari Pal, Singh Sonali, Sinha Anshita, and Sohail Shekh Mohammad. "Medical chatbot using AI and NLP." i-manager’s Journal on Software Engineering 16, no. 3 (2022): 46. http://dx.doi.org/10.26634/jse.16.3.18551.

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The use of chatbots has grown rapidly across industries, including marketing, assistive systems, education, healthcare, cultural heritage, and entertainment. This paper discusses the incentives for using chatbots and explains how useful chatbots are in various contexts. As intelligent software and hardware, also known as intelligent agents, are developed and analyzed, Artificial Intelligence (AI) is becoming more and more integrated into daily lives. From manual labor to complex procedures, intelligent agents are capable of performing a wide range of tasks. One of the simplest and most common

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Hongbing, Li, Meng Bo, and Chen Shifu. "An Agent-Based Approach for Constructing Software Systems of Virtual Simulation." International Journal of Virtual Reality 4, no. 4 (January 1, 2000): 97–109. http://dx.doi.org/10.20870/ijvr.2000.4.4.2659.

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The design and construction of virtual reality environments involve technologies such as computer graphics, image processing, pattern recognition, intelligent interface, artificial intelligence, voice recognition, network, parallel processing, and high-performance computing. Some researchers insist that object-oriented and agent-oriented technologies are fundamental for virtual reality system design. This paper applies artificial intelligence to the design of virtual reality systems. Agents are constructed by using object-oriented methods and a set of underlying computing models, such as neura

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Weinbaum (Weaver), David, and Viktoras Veitas. "Open ended intelligence: the individuation of intelligent agents." Journal of Experimental & Theoretical Artificial Intelligence 29, no. 2 (May 24, 2016): 371–96. http://dx.doi.org/10.1080/0952813x.2016.1185748.

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Karatza, H. D. "Intelligent software agents' influence on media-based systems." IEEE Distributed Systems Online 5, no. 3 (March 2004): 1–3. http://dx.doi.org/10.1109/mdso.2004.1285881.

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Fougères, Alain-Jérôme, and Egon Ostrosi. "Intelligent agents for feature modelling in computer aided design." Journal of Computational Design and Engineering 5, no. 1 (November 6, 2017): 19–40. http://dx.doi.org/10.1016/j.jcde.2017.11.001.

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Abstract CAD modelling can be referred to as the process of generating an integrated multiple view model as a representation of multiple views of engineering design. In many situations, a change in the model of one view may conflict with the models of other views. In such situations, the model of some views needs to be adapted in order to make all models consistent. Thus, CAD models should be capable of adapting themselves to new situations. Recently, agent based technologies have been considered in order to increase both knowledge level and intelligence of real and virtual objects. The contri

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MASCARDI, VIVIANA, MAURIZIO MARTELLI, and LEON STERLING. "Logic-based specification languages for intelligent software agents." Theory and Practice of Logic Programming 4, no. 04 (June 7, 2004): 429–94. http://dx.doi.org/10.1017/s1471068404002029.

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12

Moise, Gabriela. "A Software System for Online Learning Applied in the Field of Computer Science." International Journal of Computers Communications & Control 2, no. 1 (January 1, 2007): 84. http://dx.doi.org/10.15837/ijccc.2007.1.2340.

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<p>The computer-assisted learning is a very modern study area, which can be applied to the learning process. The main objective of this paper is to present a software system for online learning based on the intelligent software agents technologies. The main ideas on which this paper is built are: to any person is associated a learning profile (the idea is based on the existence of multiple intelligences, defined by Gardner [3]); the pedagogical resources can be shaped through educational semantic networks or through conceptual maps; a flexible software system in computer assisted learnin

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HAGRAS, H., V. CALLAGHAN, and M. COLLEY. "Intelligent embedded agents." Information Sciences 171, no. 4 (May 13, 2005): 289–92. http://dx.doi.org/10.1016/j.ins.2004.09.006.

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Ng, Y. C., K. S. Tey, K. R. Subramanian, S. B. Tor, L. P. Khoo, and S. G. Lee. "An Intelligent, Multi-Agent Environment for Concurrent and Collaborative Configuration of Personal Computers." Concurrent Engineering 10, no. 2 (June 2002): 143–51. http://dx.doi.org/10.1177/1063293x02010002639.

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Although Concurrent and Collaborative Engineering (CCE) has enjoyed widespread acceptance in industry, many implementation problems remain. With the advent of more powerful artificial intelligence techniques, CCE can be further improved. This paper demonstrates how intelligent software agents may be deployed to facilitate concurrent, collaborative engineering. A system architecture, Java Agent Alive!, is presented as a multi-agent environment. A case study of configuring a personal computer (PC) from its processor, memory and hard disk drive is discussed to highlight the power of software agen

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Farzaneh, Mandana, Iman Raeesi Vanani, and Babak Sohrabi. "Utilization of Intelligent Software Agent Features for Improving E-Learning Efforts." International Journal of Virtual and Personal Learning Environments 3, no. 1 (January 2012): 55–68. http://dx.doi.org/10.4018/ijvple.2012010104.

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E-learning is one of the most important learning approaches within which intelligent software agents can be efficiently used so as to automate and facilitate the process of learning. The aim of this paper is to illustrate a comprehensive categorization of intelligent software agent features, which is valuable for being deployed in the virtual world of learning and training. The characteristics of agents make them worthwhile for being used in the implementation and improvement of e-learning information systems, especially the web-based or web-enabled e-learning mechanisms. An extensive explorat

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PRAKKEN, HENRY. "Formal systems for persuasion dialogue." Knowledge Engineering Review 21, no. 2 (June 2006): 163–88. http://dx.doi.org/10.1017/s0269888906000865.

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This article reviews formal systems that regulate persuasion dialogues. In such dialogues two or more participants aim to resolve a difference of opinion, each trying to persuade the other participants to adopt their point of view. Systems for persuasion dialogue have found application in various fields of computer science, such as non-monotonic logic, artificial intelligence and law, multi-agent systems, intelligent tutoring and computer-supported collaborative argumentation. Taking a game-theoretic view on dialogue systems, this review proposes a formal specification of the main elements of

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Barfield, Woodrow. "Issues of Law for Software Agents within Virtual Environments." Presence: Teleoperators and Virtual Environments 14, no. 6 (December 2005): 741–48. http://dx.doi.org/10.1162/105474605775196607.

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A software agent is a computer program that operates within computing environments. The owners of software agents may instruct their agents to roam the networks, access desired information by exchanging data with other agents or people, and handle business and personal transactions. As the interactions between software agents and humans become more frequent, it is relevant to ask whether there are any issues of law that may guide their interactions and conduct. For example, as the agents become more intelligent and autonomous, who will be responsible for the mistakes that software agents make?

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Hoey, Jesse, Tobias Schröder, Jonathan Morgan, Kimberly B. Rogers, Deepak Rishi, and Meiyappan Nagappan. "Artificial Intelligence and Social Simulation: Studying Group Dynamics on a Massive Scale." Small Group Research 49, no. 6 (October 3, 2018): 647–83. http://dx.doi.org/10.1177/1046496418802362.

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Recent advances in artificial intelligence and computer science can be used by social scientists in their study of groups and teams. Here, we explain how developments in machine learning and simulations with artificially intelligent agents can help group and team scholars to overcome two major problems they face when studying group dynamics. First, because empirical research on groups relies on manual coding, it is hard to study groups in large numbers (the scaling problem). Second, conventional statistical methods in behavioral science often fail to capture the nonlinear interaction dynamics

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Schlimmer, J. C., and L. A. Hermens. "Software Agents: Completing Patterns and Constructing User Interfaces." Journal of Artificial Intelligence Research 1 (November 1, 1993): 61–89. http://dx.doi.org/10.1613/jair.25.

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To support the goal of allowing users to record and retrieve information, this paper describes an interactive note-taking system for pen-based computers with two distinctive features. First, it actively predicts what the user is going to write. Second, it automatically constructs a custom, button-box user interface on request. The system is an example of a learning-apprentice software- agent. A machine learning component characterizes the syntax and semantics of the user's information. A performance system uses this learned information to generate completion strings and construct a user interf

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Fortino, Giancarlo, and Antonio Guerrieri. "Decentralized management of building indoors through embedded software agents." Computer Science and Information Systems 9, no. 3 (2012): 1331–59. http://dx.doi.org/10.2298/csis120101030f.

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In order to support personalized people comfort and building energy efficiency as well as safety, emergency, and context-aware information exchange scenarios, next-generation buildings will be smart. In this paper we propose an agent-oriented decentralized and embedded architecture based on wireless sensor and actuator networks (WSANs) for enabling efficient and effective management of buildings. The main objective of the proposed architecture is to fully support distributed and coordinated sensing and actuation operations. The building management architecture is implemented at the WSAN side t

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Kieltyka, Leszek. "Knowledge Management in Multimedia Communication Using Software Agents." European Conference on Knowledge Management 24, no. 1 (September 5, 2023): 666–72. http://dx.doi.org/10.34190/eckm.24.1.1480.

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This paper presents the problem of knowledge management related to software agents and agent systems (i.e. systems composed of communicating and cooperating software agents). The author presents basic theoretical issues, but the main focus is on the areas of application of software agents in multimedia communication - both existing and prospective applications. Particular attention has been paid to the applications of software agents for: supporting customer service processes through the Contact Centre system; supporting the distance learning system; creating virtual assistants in the form of

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Yampolskiy, Roman V. "Utility function security in artificially intelligent agents." Journal of Experimental & Theoretical Artificial Intelligence 26, no. 3 (April 8, 2014): 373–89. http://dx.doi.org/10.1080/0952813x.2014.895114.

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23

Torres, Daniel. "On virtual environments and agents in next-generation computer games." Knowledge Engineering Review 23, no. 4 (December 2008): 389–97. http://dx.doi.org/10.1017/s0269888908000040.

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AbstractThis paper holds the material presented at our keynote at the Intelligent Virtual Environments and Virtual Agents Conference, where we analyzed future trends in virtual agent and environment technologies, as applied to the fields of videogames and interactive multimedia. We begin by observing current tendencies in game development projects, both in the market and in the academia, outlining their respective strengths and weaknesses. We follow by describing the aspects of game development that will come to shape the next generation of games, and discuss the requirements for academic proj

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Adomavicius, Gediminas, Alok Gupta, and Dmitry Zhdanov. "Designing Intelligent Software Agents for Auctions with Limited Information Feedback." Information Systems Research 20, no. 4 (December 2009): 507–26. http://dx.doi.org/10.1287/isre.1080.0172.

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Caro, Manuel Fernando, Darsana P. Josyula, Dalia Patricia Madera, Catriona M. Kennedy, and Adán A. Gómez. "The CARINA Metacognitive Architecture." International Journal of Cognitive Informatics and Natural Intelligence 13, no. 4 (October 2019): 71–90. http://dx.doi.org/10.4018/ijcini.2019100104.

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Metacognition has been used in artificial intelligence to increase the level of autonomy of intelligent systems. However, the design of systems with metacognitive capabilities is a difficult task due to the number and complexity of processes involved. The main objective of this article is to introduce a novel metacognitive architecture for monitoring and control of reasoning failures in artificial intelligent agents. CARINA metacognitive architecture is based on precise definitions of structural and functional elements of metacognition as defined in the MISM meta-model. CARINA can be used to i

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Jávor, András, and Attila Fűr. "Simulation on the Web with distributed models and intelligent agents." SIMULATION 88, no. 9 (July 2, 2012): 1080–92. http://dx.doi.org/10.1177/0037549712450359.

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Simulation is aimed very often to solve problems of great complexity requiring – beyond using the advanced simulation software tools – platforms that enable the implementation of such software systems. In recent years the concept of cloud computing has emerged and is being applied more and more widely for solving such problems. This paper, beyond delineating the main trends of the development of distributed simulation over a grid, especially over the Internet through Web-based applications, highlights the concepts of service-based simulation system approach. This concept gives the possibility

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Cao, Junwei, Daniel P. Spooner, Stephen A. Jarvis, and Graham R. Nudd. "Grid load balancing using intelligent agents." Future Generation Computer Systems 21, no. 1 (January 2005): 135–49. http://dx.doi.org/10.1016/j.future.2004.09.032.

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Sklar, Elizabeth, and Debbie Richards. "Agent-based systems for human learners." Knowledge Engineering Review 25, no. 2 (June 2010): 111–35. http://dx.doi.org/10.1017/s0269888910000044.

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AbstractApplying intelligent agent technologies to support human learning activities has been the subject of recent work that reaches across computer science and education disciplines. This article discusses agent-based approaches that have been designed to address a range of pedagogical and/or curricular tasks. Three types of agents are identified in the literature:pedagogical agents,peer-learning agents, anddemonstrating agents. Features of each type are considered, as well as the systems in which these agents are incorporated, examining common and divergent goals, system and agent architect

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Mateos, Cristian, Alejandro Zunino, and Marcelo Campo. "Integrating Intelligent Mobile Agents with Web Services." International Journal of Web Services Research 2, no. 2 (April 2005): 85–103. http://dx.doi.org/10.4018/jwsr.2005040105.

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Herrero, Pilar, and Angélica de Antonio. "Intelligent virtual agents keeping watch in the battlefield." Virtual Reality 8, no. 3 (February 23, 2005): 185–93. http://dx.doi.org/10.1007/s10055-004-0148-7.

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Бождай, Александр, Aleksandr Bozhday, Александр Бершадский, Aleksandr Bershadskiy, Вардан Мкртчан, and Vardan Mkrtchan. "Knowledge management methods in next-generation E/U Learning systems." Russian Journal of Management 3, no. 4 (August 31, 2015): 352–60. http://dx.doi.org/10.12737/13099.

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The article discusses the methods of knowledge management for E/U-Learning systems, which will provide the opportunities for the construction of a unified all-pervasive electronic educational environment. Authors analyze the development of a new phase of e-learning (E-Learning 3.0) in which will play an important role distributed computer systems, cloud computing, mobile personal devices and wireless networks, artificial intelligence and virtual reality tools. Today, there is a fundamental scientific problem of creating a unified interstate intellectual environment for e-education services. Th

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Ganzha, Maria. "Book Review: E-learning with Intelligent Agents [review of "Designing Distributed Learning Environments with Intelligent Software Agents" (Lin, F.O., ed.; 2004)]." IEEE Distributed Systems Online 9, no. 2 (February 2008): 4. http://dx.doi.org/10.1109/mdso.2008.6.

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Yager, Ronald R. "Intelligent agents for World Wide Web advertising decisions." International Journal of Intelligent Systems 12, no. 5 (May 1997): 379–90. http://dx.doi.org/10.1002/(sici)1098-111x(199705)12:5<379::aid-int2>3.0.co;2-k.

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Sankaranarayanan, Suresh, and Subramaniam Ganesan. "Applications of Intelligent Agents in Health Sector-A Review." International Journal of E-Health and Medical Communications 7, no. 1 (January 2016): 1–30. http://dx.doi.org/10.4018/ijehmc.2016010101.

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Health sector is a growing field and health conscience has been a major concern for everyone. Particularly in the health care sector, Information and communication Technology, enabled devices like Smart phones, Tablet PC, Sensors, RFID etc are predominantly used for ease of access and use towards decision processing. So looking into expectations of making devices smarter and intelligent enough for health care application, there has been a growing interest in the use of Software agents in health care application. This Survey paper predominantly concentrates on showing the usage and application

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Haynes, Steven R., Mark A. Cohen, and Frank E. Ritter. "Designs for explaining intelligent agents." International Journal of Human-Computer Studies 67, no. 1 (January 2009): 90–110. http://dx.doi.org/10.1016/j.ijhcs.2008.09.008.

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Melekhin, V. B., and M. V. Khachumov. "Instrumental Means for Managing the Rational Behavior of Self-Organizing Autonomous Intelligent Agents." Mekhatronika, Avtomatizatsiya, Upravlenie 22, no. 4 (April 5, 2021): 171–80. http://dx.doi.org/10.17587/mau.22.171-180.

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We formulate the basic principles of constructing a sign-signal control for the expedient behavior of autonomous intelligent agents in a priori undescribed conditions of a problematic environment. We clarify the concept of a self-organizing autonomous intelligent agent as a system capable of automatic goal-setting when a certain type of conditional and unconditional signal — signs appears in a problem environment. The procedures for planning the expedient behavior of autonomous intelligent agents have been developed, that imitate trial actions under uncertainty in the process of studying the r

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Ivanovic, Mirjana, Zoran Budimac, Milos Radovanovic, Vladimir Kurbalija, Weihui Dai, Costin Bădică, Mihaela Colhon, Srdjan Ninkovic, and Dejan Mitrovic. "Emotional agents - state of the art and applications." Computer Science and Information Systems 12, no. 4 (2015): 1121–48. http://dx.doi.org/10.2298/csis141026047i.

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last decade, intensive research on emotional intelligence has advanced significantly from its theoretical basis, analytical studies and processing technology to exploratory applications in a wide range of real-life domains. This paper brings new insights in the field of emotional, intelligent software agents. The first part is devoted to an overview of the state-of-the-art in emotional intelligence research with emphasis on emotional agents. A wide range of applications in different areas like modeling emotional agents, aspects of learning in emotional environments, interactive emotional syste

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Sbodio, Marco Luca, David Martin, and Claude Moulin. "Discovering Semantic Web services using SPARQL and intelligent agents." Journal of Web Semantics 8, no. 4 (November 2010): 310–28. http://dx.doi.org/10.1016/j.websem.2010.05.002.

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Selva, Deepaa, Balakrishnan Nagaraj, Danil Pelusi, Rajendran Arunkumar, and Ajay Nair. "Intelligent Network Intrusion Prevention Feature Collection and Classification Algorithms." Algorithms 14, no. 8 (July 26, 2021): 224. http://dx.doi.org/10.3390/a14080224.

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Rapid Internet use growth and applications of diverse military have managed researchers to develop smart systems to help applications and users achieve the facilities through the provision of required service quality in networks. Any smart technologies offer protection in interactions in dispersed locations such as, e-commerce, mobile networking, telecommunications and management of network. Furthermore, this article proposed on intelligent feature selection methods and intrusion detection (ISTID) organization in webs based on neuron-genetic algorithms, intelligent software agents, genetic alg

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BODANESE, ELIANE L., and LAURIE G. CUTHBERT. "APPLYING INTELLIGENT SOFTWARE AGENTS IN A DISTRIBUTED CHANNEL ALLOCATION SCHEME FOR CELLULAR NETWORKS." International Journal of Pattern Recognition and Artificial Intelligence 16, no. 08 (December 2002): 1021–39. http://dx.doi.org/10.1142/s0218001402002131.

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As the demand for mobile services has increased, the need for an efficient allocation of channels is essential to ensure good performance, given the limited spectrum available. Techniques for increasing flexibility in radio resource acquisition are needed to handle the heterogeneity of services and bit rates to be supported in the forthcoming generations of mobile communications. To improve the performance and efficiency of the channel allocation, we propose the use of a particular agent architecture that allows base stations to be more flexible and intelligent, including planning to attempt t

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HAYES-ROTH, BARBARA. "A domain-specific software architecture for a class of intelligent patient monitoring agents." Journal of Experimental & Theoretical Artificial Intelligence 8, no. 2 (April 1996): 149–71. http://dx.doi.org/10.1080/095281396147438.

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Elofson, G. "Intelligent agents extend knowledge-based systems feasibility." IBM Systems Journal 34, no. 1 (1995): 78–95. http://dx.doi.org/10.1147/sj.341.0078.

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Ziemke, Tom. "Adaptive Behavior in Autonomous Agents." Presence: Teleoperators and Virtual Environments 7, no. 6 (December 1998): 564–87. http://dx.doi.org/10.1162/105474698565947.

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This paper provides an overview of the bottom-up approach to artificial intelligence (AI), commonly referred to as behavior-oriented AI. The behavior-oriented approach, with its focus on the interaction between autonomous agents and their environments, is introduced by contrasting it with the traditional approach of knowledge-based AI. Different notions of autonomy are discussed, and key problems of generating adaptive and complex behavior are identified. A number of techniques for the generation of behavior are introduced and evaluated regarding their potential for realizing different aspects

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Keeble, R. J., and R. D. Macredie. "Assistant agents for the world wide web intelligent interface design challenges." Interacting with Computers 12, no. 4 (February 2000): 357–81. http://dx.doi.org/10.1016/s0953-5438(99)00004-1.

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Wolgast, Thomas, Nils Wenninghoff, Stephan Balduin, Eric Veith, Bastian Fraune, Torben Woltjen, and Astrid Nieße. "ANALYSE — Learning to attack cyber–physical energy systems with intelligent agents." SoftwareX 23 (July 2023): 101484. http://dx.doi.org/10.1016/j.softx.2023.101484.

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King, Roger L., Samuel H. Russ, Aric B. Lambert, and Donna S. Reese. "An artificial immune system model for intelligent agents." Future Generation Computer Systems 17, no. 4 (January 2001): 335–43. http://dx.doi.org/10.1016/s0167-739x(99)00115-6.

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Persson, P., J. Laaksolahti, and P. Lonnqvist. "Understanding socially intelligent agents - a multilayered phenomenon." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 31, no. 5 (2001): 349–60. http://dx.doi.org/10.1109/3468.952710.

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Zafar Jafarov, Konstantin Barabanov, Zafar Jafarov, Konstantin Barabanov. "PURPOSE AND ADVANTAGES OF CHATBOTS." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 42, no. 07 (May 25, 2024): 114–22. http://dx.doi.org/10.36962/pahtei42072024-13.

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Digital technologies, in particular chatbots, are becoming a key element of interaction between companies (brands) and consumers, performing various functions, replacing a person and imitating his behavior. They find new functional areas related to the current activities of the organization, acquire new competencies that affect the level of market flexibility of the business and its operational efficiency. Chatbots can guide shoppers through transactional steps, saving them cognitive effort and time, and become an asset that differentiates a company or brand from its competitors. The authors b

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Benoudifa, Ouafae, Abderrahim Ait Wakrime, and Redouane Benaini. "Autonomous solution for Controller Placement Problem of Software-Defined Networking using MuZero based intelligent agents." Journal of King Saud University - Computer and Information Sciences 35, no. 10 (December 2023): 101842. http://dx.doi.org/10.1016/j.jksuci.2023.101842.

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TURNER, ROY M. "Context-mediated behavior for intelligent agents." International Journal of Human-Computer Studies 48, no. 3 (March 1998): 307–30. http://dx.doi.org/10.1006/ijhc.1997.0173.

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