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Dynamic scheduling for agent based manufacturing systems

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Języki publikacji
EN
Abstrakty
EN
Purpose: Development of the decision making architecture for the multi-agent societies with temporal restrictions. General ideas for the necessary architecture based on the blackboard one is presented. Design/methodology/approach: Fuzzy logic approach that makes it possible to reach suboptimal solutions within the acceptable timeframe. Development of the relevant systems calls for compiling the experience gathered over the years in the system served by human ‘agents’. Multiagent systems negotiation needs were analysed and cooperation issues in the form of clustering, cloning, and learning were analysed in search for the relevant tools. Findings: Detailed review of the approach to development of the agent based Intelligent Manufacturing from the fundamental considerations to the latest hands-on developments. Research limitations/implications: Many presented technologies call for detailed study before they can be implemented in practice. Originality/value: Analysis of the local interactions among agents meeting the real-time reaction requirements.
Rocznik
Strony
66--69
Opis fizyczny
Bibliogr. 18 poz., rys., tabl.
Twórcy
autor
  • Division of Materials Processing Technology, Management and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18a, 44-100 Gliwice, Poland, janusz.madejski@polsl.pl
Bibliografia
  • [1] L. Hernández, V. Botti, A. García-Fornes, A deliberative scheduling technique for a real-time agent architecture, Engineering Applications of Artificial Intelligence 19/5 (2006) 521-534.
  • [2] Kun-Yung Lu, Chun-Chin Sy, A real-time decision-making of maintenance using fuzzy agent, Expert Systems with Applications 36/2 (2009) 2691-2698.
  • [3] Y. Jiang, T. Ishida, A model for collective strategy diffusion in agent social law evolution, Proceedings of the 20th International Joint Conference on “Artificial Intelligence IJCAI’07”, Hyderabad, India, 2007, 125-132.
  • [4] Yichuan Jiang, Toru Ishida, Local interaction and non-local coordination in agent social law diffusion, Expert Systems with Applications 34/1 (2008) 87-95.
  • [5] K. J. Wróblewski, R. Krawczyński, A. Kosieradzka, S. Kasprzyk, Priority rules in production flow control, WNT, Warsaw, 1984 (in Polish).
  • [6] N. Jennings, M. Wooldridge, Applications of Intelligent Agents, in: N. Jennings, M. Wooldridge (Eds.), Agent Technology. Foundations, Applications, and Markets, Springer-Verlag, 1998, 3-28.
  • [7] K. J. Wróblewski, Fundamentals of production flow control, WNT, Warsaw, 1993 (in Polish).
  • [8] J. Madejski, Agents as building blocks of responsibility-based manufacturing systems, Elsevier, (ref no PROTEC 4585 - 27 June 2000).
  • [9] L. Interrante, S. Goldsmith, Emergent Agent-Based Scheduling of Manufacturing Systems, in: Working Notes of the Agent- Based Manufacturing Workshop, Minneapolis, 1998.
  • [10] B. Burmeister, S. Bussmann, A. Haddadi, K. Sundermeyer, Agent-Oriented Techniques for Traffic and Manufacturing Applications: Progress Report, in: N. Jennings, M. Wooldridge (Eds.), Agent Technology. Foundations, Applications, and Markets, Springer-Verlag, 1998, 161-174.
  • [11] S. Ossovski, Co-ordination in Artificial Agent Societies. Social Structure and Its Implications for Autonomous Problem-Solving Agents, Springer-Verlag, 1999.
  • [12] C. Meloni, Autonomous agents architectures and algorithms in flexible manufacturing systems, in: IIE Transactions 32/10 (2000) 941-951.
  • [13] L. Kerschberg, Knowledge Rovers: Cooperative Intelligent Agent Support for Enterprise Information Architectures, in: P. Kandzia, M. Klusch (Eds.), Cooperative Information Agents, Proceedings of the 1st International Workshop, CIA’97, Kiel, Germany, Springer-Verlag, 1997, 79-100.
  • [14] T. Ohko, K. Hiraki, Y. Anzai, Addressee Learning and Message Interception for Communication Load Reduction in Multiple Robot Environments, G. Weiss (Ed.) Distributed Artificial Intelligence Meets Machine Learning. Learning in Multi-Agent Environments, ECAI’96 Workshop LDAIS, Budapest, Hungary, 1996 and ICMAS’96 Workshop LIOME, Kyoto, Japan, 1996, Springer-Verlag 1997, 242-258.
  • [15] J. Madejski, Survey of the Agent-Based Aproach to Intelligent Manufacturing, Journal of Achievements in Materials and Manufacturing Engineering 21/1 (2007) 67-70.
  • [16] R. C Arkin, T. Balch, Cooperative Multiagent Robotic Systems, in D. Kortenkamp, R.P. Bonasso, R. Murphy (Eds.), Artificial Intelligence and Mobile Robots, AAAI Press / The MIT Press, 1998, 277-296.
  • [17] T. Schael, Workflow Management Systems for Process Organisations, Springer-Verlag, 1998.
  • [18] J. Madejski , Modelling of the Manufacturing System Objects Interactions, Journal of Achievements in Materials and Manufacturing Engineering 24/2 (2007) 167-170.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BOS2-0022-0058
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