Article

Prometheus: a methodology for developing intelligent agents

Authors:

Lin Padgham,

Michael WinikoffAuthors Info & Claims

AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1

Pages 37 - 38

https://doi.org/10.1145/544741.544749

Published: 15 July 2002 Publication History

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Abstract

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References

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Marcondes FAlmeida JNovais PAgmon NAn BRicci AYeoh W(2023)SE4AI Issues on Social Media Agent Design with Use CasesProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598979(2493-2495)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598979
Guan JMorris A(2023)Design Frameworks for Hyper-Connected Social XRI Immersive Metaverse EnvironmentsIEEE Network10.1109/MNET.005.230012937:4(12-21)Online publication date: Jul-2023
https://doi.org/10.1109/MNET.005.2300129
Olan FOgiemwonyi Arakpogun ESuklan JNakpodia FDamij NJayawickrama U(2022)Artificial intelligence and knowledge sharing: Contributing factors to organizational performanceJournal of Business Research10.1016/j.jbusres.2022.03.008145(605-615)Online publication date: Jun-2022
https://doi.org/10.1016/j.jbusres.2022.03.008
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Index Terms

Prometheus: a methodology for developing intelligent agents
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Intelligent agents
      2. Multi-agent systems
2. Software and its engineering
  1. Software creation and management
    1. Designing software
      1. Software implementation planning
        Software design techniques
    2. Software development process management

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Published In

AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1

July 2002

540 pages

ISBN:1581134800

DOI:10.1145/544741

Conference Chairs:
Maria Gini
University of Minnesota, USA
,
Toru Ishida
Kyoto University, Japan
,
Program Chairs:
Cristiano Castelfranchi
CNR and Università di Siena, Italy
,
W. Lewis Johnson
University of Southern California, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 July 2002

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AAMAS02

Sponsor:

AAMAS02: The First International Joint Conference on Autonomous Agents and Multi-Agent Systems ( formerly known as Autonomous Agents )

July 15 - 19, 2002

Bologna, Italy

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Marcondes FAlmeida JNovais PAgmon NAn BRicci AYeoh W(2023)SE4AI Issues on Social Media Agent Design with Use CasesProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598979(2493-2495)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598979
Guan JMorris A(2023)Design Frameworks for Hyper-Connected Social XRI Immersive Metaverse EnvironmentsIEEE Network10.1109/MNET.005.230012937:4(12-21)Online publication date: Jul-2023
https://doi.org/10.1109/MNET.005.2300129
Olan FOgiemwonyi Arakpogun ESuklan JNakpodia FDamij NJayawickrama U(2022)Artificial intelligence and knowledge sharing: Contributing factors to organizational performanceJournal of Business Research10.1016/j.jbusres.2022.03.008145(605-615)Online publication date: Jun-2022
https://doi.org/10.1016/j.jbusres.2022.03.008
Nguyen JPowers SUrquhart NFarrenkopf TGuckert M(2022)Multi-Agent Modelling Notation (MAMN): A Multi-layered Graphical Modelling Notation for Agent-Based SimulationsPRIMA 2022: Principles and Practice of Multi-Agent Systems10.1007/978-3-031-21203-1_42(640-649)Online publication date: 12-Nov-2022
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Guedes GVicari R(2022)Specific UML-Derived Languages for Modeling Multi-agent SystemsHandbook on Artificial Intelligence-Empowered Applied Software Engineering10.1007/978-3-031-08202-3_9(159-223)Online publication date: 4-Sep-2022
https://doi.org/10.1007/978-3-031-08202-3_9
Oliva-Felipe LVerdaguer MPoch MVázquez-Salceda JCortés U(2021)The Organisational Structure of an Agent-Based Model for the Management of Wastewater SystemsWater10.3390/w1309125813:9(1258)Online publication date: 30-Apr-2021
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Fortino GGravina RRusso WSavaglio CWasielewska KGanzha MPaprzycki MPawłowski WSzmeja PTkaczyk R(2021)INTER-Meth: A Methodological Approach for the Integration of Heterogeneous IoT SystemsInteroperability of Heterogeneous IoT Platforms10.1007/978-3-030-82446-4_7(195-230)Online publication date: 14-Dec-2021
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Wang TDong HLesser VZhang CDaumé HSingh A(2020)ROMAProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525854(9876-9886)Online publication date: 13-Jul-2020
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Linnenberg TFay A(2018)Software engineering for agent based energy systems2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)10.1109/COASE.2018.8560487(174-180)Online publication date: Aug-2018
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Talib AAlomary F(2018)An Interactive Distance Education and E-Learning System Based on Multi Agent System Architecture2018 1st International Conference on Computer Applications & Information Security (ICCAIS)10.1109/CAIS.2018.8441984(1-6)Online publication date: Apr-2018
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