Academic literature on the topic 'Intelligent Software Agent'

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Journal articles on the topic "Intelligent Software Agent"

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Cohen, Mark A., Frank E. Ritter, and Steven R. Haynes. "Applying Software Engineering to Agent Development." AI Magazine 31, no. 2 (July 28, 2010): 25. http://dx.doi.org/10.1609/aimag.v31i2.2214.

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Developing intelligent agents and cognitive models is a complex software engineering activity. This article shows how all intelligent agent creation tools can be improved by taking advantage of established software engineering principles such as high-level languages, maintenance-oriented development environments, and software reuse. We describe how these principles have been realized in the Herbal integrated development environment, a collection of tools that allows agent developers to exploit modern software engineering principles.
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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 collaboration interactions, and a reusable set of software components for structuring agents. The system architecture has three types of agents: Interface agents interact with the user receiving user specifications and delivering results. They acquire, model, and utilize user preferences to guide system coordination in support of the user's tasks. Task agents help users perform tasks by formulating problem solving plans and carrying out these plans through querying and exchanging information with other software agents. Information agents provide intelligent access to a heterogeneous collection of information sources. We have implemented this system framework and are developing collaborating agents in diverse complex real world tasks, such as organizational decision making, investment counseling, health care and electronic commerce.
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S.Bhamra, G., A. K. Verma, and R. B. Patel. "Intelligent Software Agent Technology: An Overview." International Journal of Computer Applications 89, no. 2 (March 1, 2014): 19–31. http://dx.doi.org/10.5120/15474-4160.

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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 neural networks, genetic algorithms, expert systems, and plan managers. Some object-oriented frameworks of these computing models are presented to illustrate this approach. The example of a spaceship game will illustrate interactions among environments, agents, and underlying computing models. The approach and reusable class library presented herein can be applied to various virtual reality environment simulations and intelligent applications.
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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 properties of agents.Agent architecturescan be thought of as software engineering models of agents; researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally,agent languagesare software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper isnotintended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.
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Ifeanyi Isaiah, Achi, and Agwu Chukwuemeka Odi. "Multi Software Agent Based Intelligent Tutoring System." International Journal of Engineering Trends and Technology 20, no. 5 (February 25, 2015): 218–22. http://dx.doi.org/10.14445/22315381/ijett-v20p242.

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VIROLI, MIRKO, ALESSANDRO RICCI, and ANDREA OMICINI. "Operating instructions for intelligent agent coordination." Knowledge Engineering Review 21, no. 1 (March 2006): 49–69. http://dx.doi.org/10.1017/s0269888906000774.

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In contrast to standard approaches based on agent communication languages (ACLs), environment-based coordination is emerging as an interesting alternative for structuring interactions in multiagent systems (MASs). In particular, the notion of coordination artifacts has been proposed as an engineering methodology to build runtime abstractions effectively providing collaborating agents with specifically designed coordination tasks.In this paper, we study the semantics for the interaction of agents with coordination artifacts playing the same role of ACL semantics, that is, supporting semantic interoperability between agents developed by different parties through the connection between rationality and interaction. Our approach is rooted on the notion of operating instructions of coordination artifacts, which—as with a manual for a human exploiting a device—describe the interaction protocols the agent can follow as well as the mentalistic semantics of each single interaction. By tackling some of the most relevant issues raised in the context of ACL semantics, our framework allows intelligent, BDI-like agents to carry on complex interactions through coordination artifacts in a rational way.
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MÜLLER, JÖRG P. "Architectures and applications of intelligent agents: A survey." Knowledge Engineering Review 13, no. 4 (February 1999): 353–80. http://dx.doi.org/10.1017/s0269888998004020.

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The objective of this paper is twofold. In its first part, we survey the state of the art in research on agent architectures. The architecture of an agent describes its modules and capabilities, and how these operate together. We structure the field by investigating three important research threads, i.e. architectures for reactive agents, deliberative agents and interacting agents. Then we describe various hybrid approaches that reconcile these three threads, aiming at a combination of different features like reactivity, deliberation and the ability to interact with other agents. These approaches are contrasted with architectural issues of recent agent-based work, including software agents, softbots, believable agents, as well as commercial agent-based systems. The second part of the paper addresses software engineers and system designers who are interested in applying agent technology to their problem domains. The objective of this part is to assist these readers in deciding which agent architecture to choose for a specific application. We characterise the most important domains to which the different approaches described in the first part have been applied, propose an application-related taxonomy of agents, and give a set of guidelines to select the right agent (architecture) for a given application.
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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 agents in negotiating for the PC configuration with the best price and performance. A software agent is created and assigned to each of the PC components. These agents attend two levels of agent conferences, viz. the bidding conference and the PC component vendor's conference. At both conferences, each agent strives to offer components with the best performance and the lowest price. The agents were ascribed artificial intelligence through the Java Expert System Shell (JESS). At the end of the negotiations, five PC configurations were finalised that met the expectations of the user, who is informed of the outcome via e-mail. The strengths and limitations of the system architecture and the domain application of PC assembly, as well as means to enhance security, are also discussed. Some recommendations to further improve the limitations of Java Agent Alive! and the PC Assembly application are made.
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Telnov, Yu F., A. V. Danilov, R. I. Diveev, V. A. Kazakov, and E. V. Yaroshenko. "Development of a prototype of multi-agent system of network interaction of educational institutions." Open Education 22, no. 6 (January 14, 2019): 14–26. http://dx.doi.org/10.21686/1818-4243-2018-6-14-26.

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The aim of the researchis to develop a prototype of the intelligent multi-agent system for dynamic interaction of the intelligent agents in the integrated information and educational space to solve the problem of formation of joint educational programs by several educational institutions.Materials and methods.In modern conditions of digital transformation of education the organization of network training of students on dynamically formed educational programs in accordance with the needs of the labor market and the individual requirements of students is becoming increasingly important. It is proposed to develop a software platform based on intelligent multi-agent technology for flexible integration of educational resources and implementation of joint educational programs by several interacting educational institutions. As a basis for the development of the software prototype architecture, the specifications of the developer community for the standardization of agent technologies FIPA (the Foundation for Intelligent Physical Agents), and the software tool environment – JADE framework (Java Agent Development Network) were chosen.Results.The paper presents the architecture of intelligent multi-agent system for network interaction of educational institutions in the integrated information and educational space, which allows to dynamically forming educational programs in accordance with the requested professional competencies. The structure of the ontology of information and educational space, providing the interaction of intelligent agents, is justified, and the mechanism of its display from the OWL format to the format of the tool environment JADE, using the plugin Protege is described. The description of the software prototype, the structure of intelligent agents in the JADE format and the technology of agent interaction, based on the FIPA protocols in the process of educational programs formation is presented.Conclusion.The implementation of the multi-agent system prototype for network interaction of educational institutions allows you to quickly create educational programs in accordance with individual and group learning trajectories under the specific formed professional competence. The presented software prototype with some modification can be used for other subject areas of the digital economy, involving the dynamic formation of network structures of interaction for business partners.
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Dissertations / Theses on the topic "Intelligent Software Agent"

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Church, Lori A. "Decision support for software process management teams : an intelligent software agent approach /." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA377649.

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Thesis (M.S. in Software Engineering) Naval Postgraduate School, March 2000.
Thesis advisor(s): Michael, James Bret; Osmundson, John S. "March 2000." Includes bibliographical references (p. 111-115). Also available online.
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Hu, Yuebing, and 胡跃冰. "Consensus control of multi-agent systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B4658657X.

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Filipe, Joaquim Belo Lopes. "Normative organisational modelling using intelligent multi-agent systems." Thesis, Staffordshire University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327505.

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Rahwan, Iyad. "Interest-based negotiation in multi-agent systems." Connect to thesis, 2004. http://repository.unimelb.edu.au/10187/2885.

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Software systems involving autonomous interacting software entities (or agents) present new challenges in computer science and software engineering. A particularly challenging problem is the engineering of various forms of interaction among agents. Interaction may be aimed at enabling agents to coordinate their activities, cooperate to reach common objectives, or exchange resources to better achieve their individual objectives. This thesis is concerned with negotiation: a process through which multiple self-interested agents can reach agreement over the exchange of scarce resources. In particular, I focus on settings where agents have limited or uncertain information, precluding them from making optimal individual decisions. I demonstrate that this form of bounded-rationality may lead agents to sub-optimal negotiation agreements. I argue that rational dialogue based on the exchange of arguments can enable agents to overcome this problem. Since agents make decisions based on particular underlying reasons, namely their interests, beliefs and planning knowledge, then rational dialogue over these reasons can enable agents to refine their individual decisions and consequently reach better agreements. I refer to this form of interaction as “interested-based negotiation.” (For complete abstract open document)
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Lin, Chia-En. "A Comparison of Agent-Oriented Software Engineering Frameworks and Methodologies." Thesis, University of North Texas, 2003. https://digital.library.unt.edu/ark:/67531/metadc4411/.

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Agent-oriented software engineering (AOSE) covers issues on developing systems with software agents. There are many techniques, mostly agent-oriented and object-oriented, ready to be chosen as building blocks to create agent-based systems. There have been several AOSE methodologies proposed intending to show engineers guidelines on how these elements are constituted in having agents achieve the overall system goals. Although these solutions are promising, most of them are designed in ad-hoc manner without truly obeying software developing life-cycle fully, as well as lacking of examinations on agent-oriented features. To address these issues, we investigated state-of-the-art techniques and AOSE methodologies. By examining them in different respects, we commented on the strength and weakness of them. Toward a formal study, a comparison framework has been set up regarding four aspects, including concepts and properties, notations and modeling techniques, process, and pragmatics. Under these criteria, we conducted the comparison in both overview and detailed level. The comparison helped us with empirical and analytical study, to inspect the issues on how an ideal agent-based system will be formed.
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Martin, Cheryl Elizabeth Duty. "Adaptive decision-making frameworks for multi-agent systems." Access restricted to users with UT Austin EID, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3023557.

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Tran, Quynh Nhu Information Systems Technology &amp Management Australian School of Business UNSW. "MOBMAS - A methodology for ontology-based multi-agent systems development." Awarded by:University of New South Wales. School of Information Systems, Technology and Management, 2005. http://handle.unsw.edu.au/1959.4/24254.

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???Agent-based systems are one of the most vibrant and important areas of research and development to have emerged in information technology in the 1990s??? (Luck et al. 2003). The use of agents as a metaphor for designing and constructing software systems represents an innovative movement in the field of software engineering: ???Agent- Oriented Software Engineering (AOSE)??? (Lind 2000; Luck et al. 2003). This research contributes to the evolution of AOSE by proposing a comprehensive ontology-based methodology for the analysis and design of Multi-Agent Systems (MAS). The methodology is named MOBMAS, which stands for ???Methodology for Ontology-Based MASs???. A major improvement of MOBMAS over the existing agentoriented MAS development methodologies is its explicit and extensive support for ontology-based MAS development. Ontologies have been widely acknowledged for their significant benefits to interoperability, reusability, MAS development activities (such as system analysis and agent knowledge modelling) and MAS operation (such as agent communication and reasoning). Recognising these desirable ontology???s benefits, MOBMAS endeavours to identify and implement the various ways in which ontologies can be used in the MAS development process and integrated into the MAS model definitions. In so doing, MOBMAS has exploited ontologies to enhance its MAS development process and MAS development product with various strengths. These strengths include those ontology???s benefits listed above, and those additional benefits uncovered by MOBMAS, e.g. support for verification and validation, extendibility, maintainability and reliability. Compared to the numerous existing agent-oriented methodologies, MOBMAS is the first that explicitly and extensively investigates the diverse potential advantages of ontologies in MAS development, and which is able to implement these potential advantages via an ontology-based MAS development process and a set of ontology-based MAS model definitions. Another major contribution of MOBMAS to the field of AOSE is its ability to address all key concerns of MAS development in one methodological framework. The methodology provides support for a comprehensive list of methodological requirements, which are important to agent-oriented analysis and design, but which may not be wellsupported by the current methodologies. These methodological requirements were identified and validated by this research from three sources: the existing agent-oriented methodologies, the existing evaluation frameworks for agent-oriented methodologies and conventional system development methodologies, and a survey of practitioners and researchers in the field of AOSE. MOBMAS supports the identified methodological requirements by combining the strengths of the existing agent-oriented methodologies (i.e. by reusing and enhancing the various strong techniques and model definitions of the existing methodologies where appropriate), and by proposing new techniques and model definitions where necessary. The process of developing MOBMAS consisted of three sequential research activities. The first activity identified and validated a list of methodological requirements for an Agent Oriented Software Engineering methodology as mentioned above. The second research activity developed MOBMAS by specifying a development process, a set of techniques and a set of model definitions for supporting the identified methodological requirements. The final research activity evaluated and refined MOBMAS by collecting expert reviews on the methodology, using the methodology on an application and conducting a feature analysis of the methodology.
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House, Terry Carl. "A Model and Intelligent Software Agent for the Selection and Implementation of Open Source Software." NSUWorks, 2009. http://nsuworks.nova.edu/gscis_etd/180.

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In this study, the researcher created a model and software application for identifying the factors that are relevant in the decision making process to select and implement Open-source applications in higher education. Open-source applications provide the programming syntax to the user for customization. Unlike proprietary software, where the source code is unavailable and illegal to alter, an Open-Source Software (OSS) application authorizes the user to edit and recompile the application to meet the specific needs of the institution or organization. OSS applications are either free or purchasable for a one-time fee. The rising cost of proprietary software has motivated many academic institutions to consider implementing OSS. Many IT professionals are investigating the advantages and disadvantages of open-source applications in an attempt to mitigate expensive yearly fees, licensures and maintenance costs required by proprietary software vendors. The data collected in the study represented OSS and non-OSS enabled institutions that were members of the Council of Higher Education and Accreditation (CHEA) Organization. Of the data collected from the institutions, a portion of the information was set aside for validation purposes. The model created in this research addressed the OSS concerns in higher education by identifying the experiences, institutional characteristics, and technical systems relevant to the selection and implementation of OSS applications. The researcher used the Visual Basic .NET programming language to create the model and software application that provided academic institutions with technical OSS information and support. The Intelligent Software Agent (ISA) simplified the data analysis process by providing a Graphical User Interface (GUI) for the user to enter and receive data. The results of this research allowed institutions to specify certain criteria such as highest degree awarded, relevant characteristics, and technological factors and then receive implementation suggestions for adopting OSS applications. The validation process indicated that the tabled data in the model and generated suggestions of the ISA were statistically comparable with the data that was set-aside for validation purposes.
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Gao, Shijia. "Intelligent agent assisted decision support for family financial planning /." access full-text access abstract and table of contents, 2005. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?mphil-is-b19887735a.pdf.

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Thesis (M.Phil.)--City University of Hong Kong, 2005.
"Submitted to Department of Information Systems in partial fulfillment of the requirements for the degree of Master of Philosophy" Includes bibliographical references (leaves 114-132)
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Yeung, Chi-Ho. "Application of statistical physics on agent dynamics in multi-agent systems and resource allocation in random networks /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?PHYS%202006%20YEUNG.

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Books on the topic "Intelligent Software Agent"

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Intelligent agent software engineering. Hershey, PA: Idea Group Pub., 2003.

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NATO Advanced Study Institute on Software Agents, Agent Systems and their Applications (2010 Tangiers, Morocco). Software agents, agent systems and their applications. Amsterdam: IOS Press, 2012.

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Padgham, Lin. Developing Intelligent Agent Systems. New York: John Wiley & Sons, Ltd., 2005.

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Ronald, Ashri, and D'Inverno Mark, eds. Agent-based software development. Boston: Artech House, 2004.

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Pěchouček, Michal. Defence industry applications of autonomous agents and multi-agent systems. Basel: Birkhäuser, 2008.

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1956-, Zhong Ning, and Asia-Pacific Conference on Intelligent Agent Technology (2nd : 2000 : Maebashi, Japan), eds. Intelligent agent technology: Research and development. River Edge, New Jersey: World Scientific, 2001.

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Karl, Tuyls, ALAMAS 2006 (2006 : Brussels, Belgium), and ALAMAS 2007 (2007 : Maastricht, Netherlands), eds. Adaptive agents and multi-agent systems III: Adaptation and multi-agent learning ; 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems : revised selected papers. Berlin: Springer, 2008.

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Liu, Jiming. Multi-agent robotic systems. Boca Raton, FL: CRC Press, 2001.

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Khosla, Rajiv. Engineering intelligent hybrid multi-agent systems. Boston: Kluwer Academic Publishers, 1997.

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G, Harrison Colin, ed. Agent sourcebook. New York: Wiley, 1997.

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Book chapters on the topic "Intelligent Software Agent"

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Brenner, Walter, Rüdiger Zarnekow, and Hartmut Wittig. "Base Modules of Agent Systems." In Intelligent Software Agents, 35–151. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-80484-7_4.

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Bussmann, Stefan, Paolo Ciancarini, Keith Decker, Michael Huhns, and Michael Wooldridge. "Agent-Oriented Software Engineering." In Intelligent Agents VI. Agent Theories, Architectures, and Languages, 248–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10719619_18.

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Jennings, Nicholas R. "Agent-Oriented Software Engineering." In Multiple Approaches to Intelligent Systems, 4–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-540-48765-4_2.

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Abraham, Blanca Z., and Jose C. Aguilar. "Software Component Selection Algorithm Using Intelligent Agents." In Agent and Multi-Agent Systems: Technologies and Applications, 82–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72830-6_9.

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Garcia, Emilia, Adriana Giret, and Vicente Botti. "Towards an Evaluation Framework for MAS Software Engineering." In Intelligent Agents and Multi-Agent Systems, 197–205. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89674-6_22.

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Padgham, Lin. "Keynote Speech: Agent Oriented Software Engineering: Why and How." In Intelligent Agents and Multi-Agent Systems, 4–5. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89674-6_3.

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Padgham, Lin, and Michael Winikoff. "Prometheus: A Methodology for Developing Intelligent Agents." In Agent-Oriented Software Engineering III, 174–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36540-0_14.

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Soo, Von-Wun, and Hai-Long Cheng. "Conducting the Disambiguation Dialogues between Software Agent Sellers and Human Buyers." In Intelligent Agents and Multi-Agent Systems, 123–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45680-5_9.

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Cabrera-Paniagua, Daniel, and Claudio Cubillos. "UML-F in the Design of an Agent-Oriented Software Framework." In Intelligent Agents and Multi-Agent Systems, 121–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89674-6_15.

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Damian, Ionut, Birgit Endrass, Nikolaus Bee, and Elisabeth André. "A Software Framework for Individualized Agent Behavior." In Intelligent Virtual Agents, 437–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23974-8_51.

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Conference papers on the topic "Intelligent Software Agent"

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Nassiri, Nasser. "Software Agent in Desktop Virtual Shopping." In 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2009. http://dx.doi.org/10.1109/wi-iat.2009.362.

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Simula, Kirsti. "Intelligent software agent framework for customized mobile services." In the 4th. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1377934.1377939.

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Jin, Xin. "Ontology-based software agent for intelligent business terminal." In 2010 2nd IEEE International Conference on Information Management and Engineering. IEEE, 2010. http://dx.doi.org/10.1109/icime.2010.5478214.

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Straub, Jeremy. "Portability scenarios for intelligent robotic control agent software." In SPIE Defense + Security, edited by Eric J. Kelmelis. SPIE, 2014. http://dx.doi.org/10.1117/12.2049506.

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Sokas, Algirdas. "Software agent system controls comfort settings in the house." In The 13th International Conference on Engineering and Computer Graphics BALTGRAF-13. Vilnius Gediminas Technical University, 2015. http://dx.doi.org/10.3846/baltgraf.2015.008.

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A building can be called intelligent when it has the means for automatic control of all systems for life activities. Intelligent environments are able to support ever-changing environmental needs by automatically and dynamically adjusting their key parameters without explicit human intervention. An intelligent building can be defined as one that is able to acquire and apply knowledge about its inhabitants and their surroundings in order to adapt to the inhabitants and meet the goals of comfort and efficiency. Agents are software programs designed to act autonomously and adaptively to achieve goals defined by their human developers. These systems make use of a knowledge base and algorithms to carry out their responsibilities. This article analyses software agent system in the building environment. How does the agent control temperature and humidity in the house, how does it make decisions? The creation tasks of software agent system are solved with the help of Agent Unified Modelling Language. The collaboration diagram describes a particular situation and is useful to present objective range analysis results. Temperature and humidity measurement and access control appliances can interact with each other with defined functions. Fuzzy controller ensures the comfort situation in the room. Fuzzy logic rules in line with the method of choice are very important during system design. Study the conventional fuzzy control, which is also known as the creator of the first Mamdani fuzzy system. Logical description of the decision engine IF - THEN a rule set of fuzzy expert system to provide connections between the fuzzy variables in order to obtain the changes that occur in the input sensor. The computer program of fuzzy system is analysed. Obtained results are discussed and conclusions are made.
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Sakarkar, Gopal, and Shelke N. M. "A new classification acheme for autonomous software agent." In 2009 International Conference on Intelligent Agent & Multi-Agent Systems (IAMA 2009). IEEE, 2009. http://dx.doi.org/10.1109/iama.2009.5228063.

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Li, Yan. "Intelligent User Interface Design Based on Agent Technology." In 2009 WRI World Congress on Software Engineering. IEEE, 2009. http://dx.doi.org/10.1109/wcse.2009.262.

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Mala, D. Jeya, M. Kamalapriya, R. Shobana, and V. Mohan. "A non-pheromone based intelligent swarm optimization technique in software test suite optimization." In Multi-Agent Systems (IAMA 2009). IEEE, 2009. http://dx.doi.org/10.1109/iama.2009.5228055.

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Kehe Wu, Jing Zhou, Zhiwei Feng, and Jing Teng. "Study on multi-agent based software bus technology." In 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icicisys.2010.5658347.

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Yu, Han, Zhiqi Shen, and Chunyan Miao. "Intelligent Software Agent Design Tool Using Goal Net Methodology." In 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07). IEEE, 2007. http://dx.doi.org/10.1109/iat.2007.25.

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