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2012 | Vol. 55, nr 1 | 74--79
Tytuł artykułu

Co-ordination in the autonomous software agents’ systems

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Wybrane pełne teksty z tego czasopisma
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: Agents are designed to behave individually rational, which means that they should maximize their personal utility which is the way to make them less vulnerable to mean actions of others, yet they have to co-ordinate their actions to reach common goals, which is the purpose of this work. Design/methodology/approach: Agents can create and pursue their individual goals, behaving in a ‘selfish’ way to acquire the desired state of their world. To achieve that they may choose to adopt goals of other agents too, should this co-ordination be assessed as beneficial for them. Moreover, there is also a possibility to define the desired states of the agents in a way which will induce them to work together rather than try to operate individually. This may include their specialization, which forces in most cases sharing of their potential. This may be achieved by specialised design of agents being able to carry out elementary tasks. Such approach calls however, for design of a layer of supervisory agents which will be capable of realising what is the multi-agent overall system goal, setting up their teams from simple agents and committing to common sub-goals. All such systems may be efficiently developed only after careful study of the successfully operating systems in which humans are the agents, whose tasks may now be assigned to the software ones. These agents have to be coupled, as it also happens in their human counterparts. Findings: Development of the software agents’ co-operation framework based on review of publications covering both the fundamental considerations, as well as the latest developments. Research limitations/implications: Approach presented still needs careful testing and refinement of the co-ordination / negotiation rules. Originality/value: Co-ordination of agents to reach their common goal, satisfying also their individual utility.
Wydawca

Rocznik
Strony
74--79
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
autor
  • Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18a, 44-100 Gliwice, Poland, janusz.madejski@polsl.pl
Bibliografia
  • [1] J. Madejski, Survey of the agent-based approach to intelligent manufacturing, Journal of Achievements in Materials and Manufacturing Engineering 21/1 (2007) 67-70.
  • [2] J. Madejski, Agents as building blocks of responsibility-based manufacturing systems, Elsevier, 2000.
  • [3] J. Reaidy, P. Massotte, D. Diep, Comparison of negotiation protocols in dynamic agent-based manufacturing systems, Elsevier, International Journal of Production Economics 99 (2006) 117-130.
  • [4] T.N. Wong, C.W. Leung, K.L. Mak, R.Y.K. Fung, Dynamic shopfloor scheduling in multi-agent manufacturing systems, Expert Systems with Applications 31/3 (2006) 486-494.
  • [5] G. Gaspar, Communication and belief change in a society of agents, Towards a formal model of autonomous agent, Y. Demazeau, J.-P. Müller (Eds), Decentralized AI II, Elsevier Science Publishers B.V., Amsterdam, 1991.
  • [6] J. Campbell, M. d'Inverno, Knowledge interchange protocol, Y. Damazeau, J.-P. Müller (Eds), Decentralized AI I, Elsevier Science Publishers B.V., Amsterdam, 1990, 63-80.
  • [7] B. Burmeister, A. Haddadi, K. Sundermeyer, Generic, configurable, cooperation protocols for multi-agent systems, C. Castelfranchi, J.-P. Müller (Eds), From reaction to cognition 957, Springer Verlag, Berlin, 1995, 157-171.
  • [8] J. Madejski, Modelling of the manufacturing system objects interactions, Journal of Achievements in Materials and Manufacturing Engineering 24/2 (2007) 167-170.
  • [9] S. Sian, Adaptation based on cooperative learning in multiagent systems, Y. Demazeau, J.-P. Mülller (Eds), Decentralized AI II, Elsevier Science Publishers B.V., Amsterdam, 1991.
  • [10] J.W. Perram, Y. Damazeau, A multi-agent architecture for distributed constrained optimization and control, Proceedings of the Scandinavian Conference on Artificial Intelligence SCAl'97, G. Grahme (Ed.), IOS Press, 1997, 162-175.
  • [11] R.A. Mahdavinejad, A new approach to job shop-scheduling problem, Journal of Achievements in Materials and Manufacturing Engineering 41 (2010) 200-206.
  • [12] J. Madejski, Dynamic scheduling for agent based manufacturing systems, Journal of Achievements in Materials and Manufacturing Engineering 40/1 (2010) 66-69.
  • [13] S. Toshiharu, F. Kensuke, H. Toshio, K. Satoshi, Effect of Alternative Distributed Task Allocation Strategy Based on Local Observations in Contract Net Protocol, in N. Desai, A. Liu, M. Winikoff (Eds.): Principles and Practice of MultiAgent Systems, Proceedings of the 13th International Conference PRIMA’2010, Kolkata, 2010, Revised Selected Papers, Springer, 2012.
  • [14] D. Wang, S.V. Nagalingam, G.C.I. Lin, Development of an agent-based Virtual CIM architecture for small to medium manufacturers, Robotics and Computer-Integrated Manufacturing 23/1 (2007) 1-16.
  • [15] M.D. Reimann, J. Sarkis, An intelligent system for automating the inspection of manufacturing parts, Design and Implementation of Intelligent Manufacturing systems, from expert systems, Neural; Networks, to Fuzzy Logic, H.R. Parsaei, M. Jamshidi (Eds), Prentice Hall PTR, 1995, 19-38.
  • [16] F.P.M. Biemans, Manufacturing Planning and Control, A Reference Model, Elsevier, 1990.
  • [17] L.R. Nyman, Making manufacturing cells work, Society of Manufacturing Engineers in Cooperation with the Computer and Automated Systems, 1992.
  • [18] S. Ossowski, Co-ordination in artificial agent societies, Social Structure and Its Implications for Autonomous Problem-Solving Agents, Springer, 1999.
  • [19] J.P. Müller, The design of intelligent agents, A layered approach, Springer, 1996.
  • [20] J. Madejski, The autonomous agent-based manufacturing systems architecture, Proceedings of the Scientific Conference on the Occassion of the 55th Anniversary of the Faculty of Mechanical Engineering of the Silesian University of Technology in Gliwice M2E’2000, Gliwice, 2000, 293-302.
  • [21] J. Madejski, Fuzzy logic approach to the autonomous agent task utility function evaluation, Proceedings of the 8th International Conference on "Achievements in Mechanical and Materials Engineering" AMME'99, Rydzyna, 1999.
  • [22] H. Van Brussel, L. Bongaerts, J. Wyns, P. Valckenaers, T. Van Ginderachter, A conceptual framework for holonic manufacturing: Identification of manufacturing holons, Journal of Manufacturing Systems, Journal of Manufacturing Systems, 1999, http://findarticles.com/p/articles/mi_qa3685/is_199901/ai_n8841020/pg_1.
  • [23] A. Dobrzańska-Danikiewicz, D. Krenczyk, The selection of the production route in the assembly system, Journal of Achievements in Materials and Manufacturing Engineering 17 (2006) 417-420.
  • [24] H. Karun, P. Valckenaers, M. Kollingbaum, H. Van Brussel, Multi-agent coordination and control using stigmergy, Computers in Industry 53/1 (2004) 75-96.
  • [25] P. Bresciani, P. Giorgini, F. Giunchiglia, J. Mylopoulos, A. Perini, Tropos: An agent-oriented software development methodology, Journal of Autonomous Agents and MultiAgent Systems, 2004.
  • [26] L. Cernuzzi, G. Rossi, On the evaluation of agent oriented modeling methods, Agent Oriented Methodology Workshop, 2002.
  • [27] H. Bincheng, L. Jiming, J. Xiaolong, From local behaviors to global performance in a Multi-Agent System, Intelligent Agent Technology, 2004.
  • [28] Foundation for Intelligent Physical Agents: http://www.fipa.org.
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  • [30] Y. Peng, T. Finin, B. Chu, Y. Labrou, R.S. Cost, B. Chu, J. Long, W. Tolone, A. Boughannam, An agent-based approach for manufacturing integration, The CIIMPLEX Experience,http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.401.
Typ dokumentu
Bibliografia
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Identyfikator YADDA
bwmeta1.element.baztech-18033058-eb8e-46d7-b4d2-413547084701
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