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Journal articles on the topic 'Software Agents'

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Published: 4 June 2021
Last updated: 31 January 2023

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1

Jennings, N., and M. Wooldridge. "Software agents." IEE Review 42, no. 1 (January 1, 1996): 17–20. http://dx.doi.org/10.1049/ir:19960101.

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2

Genesereth, Michael R., and Steven P. Ketchpel. "Software agents." Communications of the ACM 37, no. 7 (July 1994): 48. http://dx.doi.org/10.1145/176789.176794.

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3

Wong, A. "Intelligent Software Agents." Computer Communications 23, no. 7 (March 2000): 695–96. http://dx.doi.org/10.1016/s0140-3664(99)00186-3.

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4

Dalmeijer, M., D. K. Hammer, and A. T. M. Aerts. "Mobile software agents." Computers in Industry 41, no. 3 (May 2000): 251–60. http://dx.doi.org/10.1016/s0166-3615(99)00047-0.

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5

LUCIA, PAVLIKOVA, BEAT F. SCHMID, MAASS WOLFGANG, and JÖRG P. MÜLLER. "Editorial: Software Agents." Electronic Markets 13, no. 1 (January 1, 2003): 1–2. http://dx.doi.org/10.1080/1019678032000062195.

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6

hemat, Monireh Azimi. "Fuzzy Content Based Image Retrieval Using Software Agents." International Academic Journal of Science and Engineering 05, no. 01 (June 1, 2018): 1–11. http://dx.doi.org/10.9756/iajse/v5i1/1810001.

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7

Morreale, P. "Agents on the move [mobile software agents]." IEEE Spectrum 35, no. 4 (April 1998): 34–41. http://dx.doi.org/10.1109/6.666958.

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8

Arsene, Octavian, Ioan Dumitrache, and Ioana Mihu. "Collaborative Medical Software Agents." IFAC Proceedings Volumes 43, no. 22 (2010): 34–39. http://dx.doi.org/10.3182/20100929-3-ro-4017.00007.

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9

Ören, Tuncer I. "Software Agents and Simulation." SIMULATION 76, no. 6 (June 2001): 328. http://dx.doi.org/10.1177/003754970107600601.

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10

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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11

Patrick, A. S. "Building trustworthy software agents." IEEE Internet Computing 6, no. 6 (November 2002): 46–53. http://dx.doi.org/10.1109/mic.2002.1067736.

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12

Nwana, Hyacinth S. "Software agents: an overview." Knowledge Engineering Review 11, no. 3 (September 1996): 205–44. http://dx.doi.org/10.1017/s026988890000789x.

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AbstractAgent software is a rapidly developing area of research. However, the overuse of the word “agent” has tended to mask the fact that, in reality, there is a truly heterogeneous body of research being carried out under this banner. This overview paper presents a typology of agents. Next, it places agents in context, defines them and then goes on, inter alia, to overview critically the rationales, hypotheses, goals, challenges and state-of-the-art demonstrators of the various agent types in our typology. Hence, it attempts to make explicit much of what is usually implicit in the agents literature. It also proceeds to overview some other general issues which pertain to all the types of agents in the typology. This paper largely reviews software agents, and it also contains some strong opinions that are not necessarily widely accepted by the agent community.
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13

CRABTREE, BARRY. "What Chance Software Agents?" Knowledge Engineering Review 13, no. 2 (July 1998): 131–36. http://dx.doi.org/10.1017/s0269888998002112.

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Software agents have come a long way in the last ten or so years. This paper looks at the practical challenges many software agent developers face including: interfacing to legacy systems; developing distributed systems; agent competence; and trust and privacy issues. Because it covers such a broad area, it will focus on how the problems and issues have changed over the years, and highlight some of the perennial problems.
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14

MILEWSKI, ALLEN E., and STEVEN H. LEWIS. "Delegating to software agents." International Journal of Human-Computer Studies 46, no. 4 (April 1997): 485–500. http://dx.doi.org/10.1006/ijhc.1996.0100.

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15

Ajith Jubilson, E., and Ravi Sankar Sangam. "Software Metrics for Computing Quality of Software Agents." Journal of Computational and Theoretical Nanoscience 17, no. 5 (May 1, 2020): 2035–38. http://dx.doi.org/10.1166/jctn.2020.8845.

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Metrics are the essential building blocks for any evaluation process. They establish specific goals for improvement. Multi agent system (MAS) is complex in nature, due to the increase in complexity of developing a multi agent system, the existing metrics are less sufficient for evaluating the quality of an MAS. This is due to the fact that agent react in an unpredictable manner. Existing metrics for measuring MAS quality fails to addresses potential communication, initiative behaviour and learn-ability. In this work we have proposed additional metrics for measuring the software agent. A software agent for online shopping system is developed and the metrics values are obtained from it and the quality of the multi agent system is analysed.
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16

FUJITA, Shigeru. "Software Agents and Digital-Jiin." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 32, no. 6 (December 15, 2020): 180–85. http://dx.doi.org/10.3156/jsoft.32.6_180.

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17

Buhler, P. A., and M. N. Huhns. "Trust and persistence [software agents]." IEEE Internet Computing 5, no. 2 (2001): 85–87. http://dx.doi.org/10.1109/4236.914652.

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18

Maamar, Zakaria, and Paul Labbé. "Moving vs. inviting software agents." Communications of the ACM 46, no. 7 (July 2003): 143–44. http://dx.doi.org/10.1145/792704.792736.

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19

Moreno, A., and C. Garbay. "Software agents in health care." Artificial Intelligence in Medicine 27, no. 3 (March 2003): 229–32. http://dx.doi.org/10.1016/s0933-3657(03)00004-6.

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20

Kephart, Jeffrey O., James E. Hanson, and Amy R. Greenwald. "Dynamic pricing by software agents." Computer Networks 32, no. 6 (May 2000): 731–52. http://dx.doi.org/10.1016/s1389-1286(00)00026-8.

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21

Rothermel, Kurt. "Guest editorial: Mobile software agents." Personal Technologies 2, no. 2 (June 1998): 47–48. http://dx.doi.org/10.1007/bf01324933.

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22

Bain, Malcolm, and Brian Subirana. "E-commerce oriented software agents." Computer Law & Security Review 19, no. 3 (May 2003): 201–11. http://dx.doi.org/10.1016/s0267-3649(03)00303-0.

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23

Bain, Malcolm, and Brian Subirana. "E-commerce oriented software agents." Computer Law & Security Review 19, no. 4 (July 2003): 282–88. http://dx.doi.org/10.1016/s0267-3649(03)00403-5.

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24

Vu Anh Pham and A. Karmouch. "Mobile software agents: an overview." IEEE Communications Magazine 36, no. 7 (July 1998): 26–37. http://dx.doi.org/10.1109/35.689628.

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25

Bădică, Costin, Zoran Budimac, Hans-Dieter Burkhard, and Mirjana Ivanovic. "Software agents: Languages, tools, platforms." Computer Science and Information Systems 8, no. 2 (2011): 255–98. http://dx.doi.org/10.2298/csis110214013b.

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The main goal of this paper is to provide an overview of the rapidly developing area of software agents serving as a reference point to a large body of literature and to present the key concepts of software agent technology, especially agent languages, tools and platforms. Special attention is paid on significant languages designed and developed in order to support implementation of agent-based systems and their applications in different domains. Afterwards, in the paper a number of useful and practically used tools and platforms that are available and support activities or phases of the process of agent-oriented software development are presented.
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26

Hexmoor, Henry, David Kortenkamp, and Ian Horswill. "Software architectures for hardware agents." Journal of Experimental & Theoretical Artificial Intelligence 9, no. 2-3 (April 1997): 145. http://dx.doi.org/10.1080/095281397147031.

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27

Hexmoor, Henry, David Kortenkamp, and Ian Horswill. "Software architectures for hardware agents." Journal of Experimental & Theoretical Artificial Intelligence 9, no. 2-3 (April 1997): 147–56. http://dx.doi.org/10.1080/095281397147040.

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28

Mahmoud, Q. H., and L. Yu. "Making Software Agents User-Friendly." Computer 39, no. 7 (July 2006): 96–95. http://dx.doi.org/10.1109/mc.2006.239.

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29

van der Meij, H. "Motivating agents in software tutorials." Computers in Human Behavior 29, no. 3 (May 2013): 845–57. http://dx.doi.org/10.1016/j.chb.2012.10.018.

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30

Costa, P. R., and L. M. Botelho. "Learning by Observation of Agent Software Images." Journal of Artificial Intelligence Research 47 (July 1, 2013): 313–49. http://dx.doi.org/10.1613/jair.3989.

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Learning by observation can be of key importance whenever agents sharing similar features want to learn from each other. This paper presents an agent architecture that enables software agents to learn by direct observation of the actions executed by expert agents while they are performing a task. This is possible because the proposed architecture displays information that is essential for observation, making it possible for software agents to observe each other. The agent architecture supports a learning process that covers all aspects of learning by observation, such as discovering and observing experts, learning from the observed data, applying the acquired knowledge and evaluating the agent's progress. The evaluation provides control over the decision to obtain new knowledge or apply the acquired knowledge to new problems. We combine two methods for learning from the observed information. The first one, the recall method, uses the sequence on which the actions were observed to solve new problems. The second one, the classification method, categorizes the information in the observed data and determines to which set of categories the new problems belong. Results show that agents are able to learn in conditions where common supervised learning algorithms fail, such as when agents do not know the results of their actions a priori or when not all the effects of the actions are visible. The results also show that our approach provides better results than other learning methods since it requires shorter learning periods.
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31

Kundu, Shakti, and M. L. "Web Data Mining through Software Agents." International Journal of Computer Applications 166, no. 5 (May 17, 2017): 44–48. http://dx.doi.org/10.5120/ijca2017914142.

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32

Шубін, Ігор Юрійович, and Ірина Віталіївна Кириченко. "SOFTWARE AGENTS IN E-LEARNING SYSTEMS." Bulletin of NTU "KhPI". Series: Strategic Management, Portfolio, Program and Project Management, no. 1(1277) (February 5, 2018): 57–63. http://dx.doi.org/10.20998/125148.

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33

T. Hawryszkiewycz, I. "Software Agents for Managing Learning Plans." Issues in Informing Science and Information Technology 3 (2006): 269–77. http://dx.doi.org/10.28945/890.

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34

Suganthy, A., and T. Chithralekha. "Domain-Specific Architecture for Software Agents." Journal of Object Technology 7, no. 6 (2008): 77. http://dx.doi.org/10.5381/jot.2008.7.6.a2.

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35

McCall, Ryan J., Stan Franklin, Usef Faghihi, Javier Snaider, and Sean Kugele. "Artificial Motivation for Cognitive Software Agents." Journal of Artificial General Intelligence 11, no. 1 (January 1, 2020): 38–69. http://dx.doi.org/10.2478/jagi-2020-0002.

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AbstractNatural selection has imbued biological agents with motivations moving them to act for survival and reproduction, as well as to learn so as to support both. Artificial agents also require motivations to act in a goal-directed manner and to learn appropriately into various memories. Here we present a biologically inspired motivation system, based on feelings (including emotions) integrated within the LIDA cognitive architecture at a fundamental level. This motivational system, operating within LIDA’s cognitive cycle, provides a repertoire of motivational capacities operating over a range of time scales of increasing complexity. These include alarms, appraisal mechanisms, appetence and aversion, and deliberation and planning.
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36

Gong, Yiwei, Sietse Overbeek, and Marijn Janssen. "Integrating Semantic Web and Software Agents." International Journal of Systems and Service-Oriented Engineering 2, no. 1 (January 2011): 60–76. http://dx.doi.org/10.4018/jssoe.2011010104.

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Software agents and rules are both used for creating flexibility. Exchanging rules between Semantic Web and agents can ensure consistency in rules and support easy updating and changing of rules. The Rule Interchange Format (RIF) is a new W3C recommendation Semantic Web standard for exchanging rules among disparate systems. Yet, the contribution of RIF in rules exchange between Semantic Web and software agents is unclear. The BDI architectural style is regarded as the predominant approach for the implementation of intelligent agents. This paper proposes a development for integrating RIF and BDI agents to enhance agent reasoning capabilities. This approach consists of an integration architecture and equivalence principles for rule translation. The equivalence principles are demonstrated using examples. The results show that the approach allows the integration of RIF with BDI agent programming and realize the translation between the two systems.
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37

Pech, Stephan. "Software Agents in Industrial Automation Systems." IEEE Software 30, no. 3 (May 2013): 20–24. http://dx.doi.org/10.1109/ms.2013.57.

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38

Inge Morisbak, Stein, and Bjornar Tessem. "Agents for case-based software reuse." Applied Artificial Intelligence 15, no. 3 (March 2001): 297–332. http://dx.doi.org/10.1080/08839510151063271.

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39

da Silva, Flavio Soares Correa, and Wamberto Weber Vasconcelos. "MANAGING RESPONSIVE ENVIRONMENTS WITH SOFTWARE AGENTS." Applied Artificial Intelligence 21, no. 4-5 (April 25, 2007): 469–88. http://dx.doi.org/10.1080/08839510701253682.

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40

Lohani, Minoo, and V. K. J. Jeevan. "Intelligent software agents for library applications." Library Management 28, no. 3 (February 27, 2007): 139–51. http://dx.doi.org/10.1108/01435120710727983.

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41

Nourani, Cyrus F. "Software agents and intelligent object fusion." ACM SIGSOFT Software Engineering Notes 23, no. 1 (January 1998): 98. http://dx.doi.org/10.1145/272263.272358.

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42

Penserini, Loris, Anna Perini, Angelo Susi, and John Mylopoulos. "High variability design for software agents." ACM Transactions on Autonomous and Adaptive Systems 2, no. 4 (November 2007): 16. http://dx.doi.org/10.1145/1293731.1293736.

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43

Lucas, Richard. "Moral Theories for Autonomous Software Agents." ACM SIGCAS Computers and Society 34, no. 1 (June 30, 2004): 4. http://dx.doi.org/10.1145/1050305.1050309.

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44

Benedicenti, Luigi, Victor Wei Wang, Peter Lee, and Raman Paranjape. "Establishing quality control in software agents." ACM SIGAPP Applied Computing Review 9, no. 3 (September 2001): 31–33. http://dx.doi.org/10.1145/570132.570137.

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45

NWANA, HYACINTH S., and DIVINE T. NDUMU. "A perspective on software agents research." Knowledge Engineering Review 14, no. 2 (September 1999): 125–42. http://dx.doi.org/10.1017/s0269888999142012.

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46

Keele, J. W., and J. E. Wray. "Software agents in molecular computational biology." Briefings in Bioinformatics 6, no. 4 (January 1, 2005): 370–79. http://dx.doi.org/10.1093/bib/6.4.370.

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47

Benfenati, Emilio, Andrey A. Toropov, Alla P. Toropova, Alberto Manganaro, and Rodolfo Gonella Diaza. "coral Software: QSAR for Anticancer Agents." Chemical Biology & Drug Design 77, no. 6 (May 4, 2011): 471–76. http://dx.doi.org/10.1111/j.1747-0285.2011.01117.x.

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48

Toomey, C., and W. Mark. "Satellite image dissemination via software agents." IEEE Expert 10, no. 5 (October 1995): 44–51. http://dx.doi.org/10.1109/64.464930.

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49

Vasilakos, A. V. "Software Agents for Future Communication Systems." Computer Communications 23, no. 18 (December 2000): 1791. http://dx.doi.org/10.1016/s0140-3664(00)00210-3.

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50

Magedanz, T., and A. Karmouch. "Mobile Software Agents for Telecommunication Applications." Computer Communications 23, no. 8 (April 2000): 705–7. http://dx.doi.org/10.1016/s0140-3664(99)00230-3.

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