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An Introduction to Multi-Agent Systems

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Innovations in Multi-Agent Systems and Applications - 1

Part of the book series: Studies in Computational Intelligence ((SCI,volume 310))

Summary

Multi-agent systems is a subfield of Distributed Artificial Intelligence that has experienced rapid growth because of the flexibility and the intelligence available solve distributed problems. In this chapter, a brief survey of multi-agent systems has been presented. These encompass different attributes such as architecture, communication, coordination strategies, decision making and learning abilities. The goal of this chapter is to provide a quick reference to assist in the design of multi-agent systems and to highlight the merit and demerits of the existing methods.

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References

  1. Jennings, N.R., Sycara, K., Woolridge, M.: A roadmap of agent research and development. Autonomous Agents and Multi-Agent Systems Journal 1(1), 7–38 (1998)

    Article  Google Scholar 

  2. Jain, L.C., Jain, R.K. (eds.): Hybrid Intelligent Engineering Systems. World Scientific Publishing Company, Singapore (1997)

    MATH  Google Scholar 

  3. Mumford, C., Jain, L.C. (eds.): Computational intelligence: Collaboration, Fusion and Emergence. Springer, Heidelberg (2009)

    MATH  Google Scholar 

  4. Fulcher, J., Jain, L.C. (eds.): Computational Intelligence: A Compendium. Springer, Heidelberg (2008)

    MATH  Google Scholar 

  5. Jain, L.C., Sato, M., Virvou, M., Tsihrintzis, G., Balas, V., Abeynayake, C. (eds.): Computational Intelligence Paradigms. Innovative Applications, vol. 1. Springer, Heidelberg (2008)

    MATH  Google Scholar 

  6. Jain, L.C., De Wilde, P. (eds.): Practical Applications of Computational Intelligence Techniques. Kluwer Academic Publishers, USA (2001)

    MATH  Google Scholar 

  7. Jain, L.C., Martin, N.M. (eds.): Fusion of Neural Networks, Fuzzy Logic and Evolutionary Computing and their Applications. CRC Press, USA (1999)

    Google Scholar 

  8. Tedorescu, H.N., Kandel, A., Jain, L.C. (eds.): Fuzzy and Neuro-fuzzy Systems in Medicine. CRC Press, USA (1998)

    Google Scholar 

  9. Khosla, R., Ichalkaranje, N., Jain, L.C. (eds.): Design of Intelligent Multi-Agent Systems. Springer, Germany (2005)

    MATH  Google Scholar 

  10. Jain, L.C., Chen, Z., Ichalkaranje, N. (eds.): Intelligent Agents and Their Applications. Springer, Germany (2002)

    MATH  Google Scholar 

  11. Resconi, G., Jain, L.C. (eds.): Intelligent Agents: Theory and Applications. Springer, Germany (2004)

    MATH  Google Scholar 

  12. Nwana, H.: Software agents: An overview. Knowledge and Engineering Review 11(3) (1996)

    Google Scholar 

  13. Vlassis, N.: A Concise introduction to multiagent systems and distributed artifical intelligence. Synthesis Lectures On Artificial Intelligence And Machine Learning, 1st edn. (2007)

    Google Scholar 

  14. Stone, P., Veloso, M.: Multiagent systems: A survey from the machine learning perspective. Autonomous Robotics 8(3), 1–56 (2000)

    Google Scholar 

  15. Ren, Z., Anumba, C.J.: Learning in multi-agent systems: a case study of construction claim negotiation. Advanced Engineering Informatics 16(4), 265–275 (2002)

    Article  Google Scholar 

  16. Goldman, C.V.: Learning in multi-agent systems. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence and the Eighth Innovative Applications of Artificial Intelligence Conference, vol. 2, p. 1363 (1996)

    Google Scholar 

  17. Alonso, E., D’Inverno, M., Kudenko, D., Luck, M., Noble, J.: Learning in multi-agent systems. The Knowledge Engineering Review 13(3), 277–284 (2001)

    Google Scholar 

  18. Bergenti, F., Ricci, A.: Three approaches to the coordination of multiagent systems. In: Proceedings of the 2002 ACM Symposium on Applied Computing, March 2002, pp. 367–373 (2002)

    Google Scholar 

  19. Hsia, T.C., Soderstrand, M.: Development of a micro robot system for playing soccer games. In: Proceedings of the Micro-Robot World Cup Soccer Tournament, pp. 149–152 (1996)

    Google Scholar 

  20. Balaji, P.G., Srinivasan, D.: Distributed multi-agent type-2 fuzzy architecture for urban traffic signal control. In: IEEE International Conference on Fuzzy Systems, pp. 1624–1632 (2009)

    Google Scholar 

  21. Parker, L.E.: Heterogeneous multi-robot cooperation. PhD Thesis, Massachusetts Institute of Technology (1994)

    Google Scholar 

  22. Parker, L.E.: Life-long adaptation in hetergeneous multi-robot teams: response to continual variation in robot performance. Autonomous Robots 8(3) (2000)

    Google Scholar 

  23. Drezewski, R., Siwik, L.: Co-evolutionary multi-agent system with predator-prey mechanism for multi-objective optimization. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds.) ICANNGA 2007. LNCS, vol. 4431, pp. 67–76. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  24. Damba, A., Watanabe, S.: Hierarchical control in a multiagent system. International Journal of innovative computing, Information & Control 4(2), 3091–3100 (2008)

    Google Scholar 

  25. Choy, M.C., Srinivasan, D., Cheu, R.L.: Neural Networks for Continuous Online Learning and Control. IEEE Transactions on Neural Networks 17(6), 1511–1531 (2006)

    Article  Google Scholar 

  26. Balaji, P.G., Sachdeva, G., Srinivasan, D., Tham, C.K.: Multi-agent system based urban traffic management. In: Proceedings of IEEE Congress on Evolutionary Computation, pp. 1740–1747 (2007)

    Google Scholar 

  27. Koestler, A.: The ghost in the machine. Hutchinson Publication Group, London (1967)

    Google Scholar 

  28. Leitao, P., Valckenaers, P., Adam, E.: Self-adaptation for robustness and cooperation in holonic multi-agent systems. In: Hameurlain, A., Küng, J., Wagner, R. (eds.) Transactions on Large-Scale Data- and Knowledge-Centered Systems I. LNCS, vol. 5740, pp. 267–288. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  29. Yadgar, O., Kraus, S., Oritz, C.: Scaling up distributed sensor networks: Cooperative large scale mobile agent organizations. In: Distributed Sensor Networks: A Multiagent Perspective, pp. 185–218 (2003)

    Google Scholar 

  30. Schillo, M., Fischer, K.: A taxanomy of autonomy in multiagent organisation. In: Nickles, M., Rovatsos, M., Weiss, G. (eds.) AUTONOMY 2003. LNCS (LNAI), vol. 2969, pp. 68–82. Springer, Heidelberg (2004)

    Google Scholar 

  31. Bongearts, L.: Integration of scheduling and control in holonic manufacturing systems. PhD Thesis. Katholieke Universiteit Leuven, Belgium (1998)

    Google Scholar 

  32. Srinivasan, D., Choy, M.C.: Distributed problem solving using evolutionary learning in multi-agent systems. Studies in Computational Intelligence, vol. 66, pp. 211–227 (2007)

    Google Scholar 

  33. Van De Vijsel, M., Anderson, J.: Coalition formation in multi-agent systems under real-world conditions. AAAI Workshop – Technical Report, v WS-04-06, pp. 54–60 (2004)

    Google Scholar 

  34. Horling, B., Lesser, V.: A survey of multi-agent organizational paradigms. Knowledge Engineering Review 19(4), 281–316 (2004)

    Article  Google Scholar 

  35. Agogino, A.K., Tumer, K.: Team formation in partially observable multi-agent systems. NASA Ames Research Center, NTIS (2004)

    Google Scholar 

  36. Budianto: An overview and survey on multi agent system, in Seminar Nasional Soft Computing, Intelligent Systems and Information Technology, SIIT 2005 (2005)

    Google Scholar 

  37. Choy, M.C., Srinivasan, D., Cheu, R.L.: Cooperative, hybrid agent architecture for real-time traffic signal control. IEEE Trans. On Systems, Man and Cybernetics-Part A: Systems and Humans 33(5), 597–607 (2003)

    Article  Google Scholar 

  38. Balaji, P.G., Srinivasan, D., Tham, C.K.: Coordination in distributed multi-agent system using type-2 fuzzy decision systems. In: Proceedings of IEEE International Conference on Fuzzy Systems, pp. 2291–2298 (2008)

    Google Scholar 

  39. Lander, S.E.: Issues in multiagent design systems. IEEE Expert 12(2), 18–26 (1997)

    Article  Google Scholar 

  40. Flores-Mendez, R.A.: Towards a standardization of multi-agent system framework. Crossroads 5(4), 18–24 (1999)

    Article  Google Scholar 

  41. Cengeloglu, Y.: A Framework for dynamic knowledge exchange among intelligent agents. In: AAAI Symposium, Control of the Physial World by Intelligent Agents (1994)

    Google Scholar 

  42. Genesereth, M., Fikes, R.: Knowledge interchange format, Version 3.0 Reference manual. Technical report, Computer Science Department, Stanford University, USA (1992)

    Google Scholar 

  43. Ginsberg, M.: The Knowledge interchange format: The KIF of death. AAAI Magazine 12(3), 57–63 (Fall 1991)

    MathSciNet  Google Scholar 

  44. Finin, T., Labrou, Y., Mayfield, J.: KQML as an agent communication language. In: Software Agents, pp. 291–316. AAAI Press, Menlo Park (1997)

    Google Scholar 

  45. Gibbons, R.: Game theory for Applied Economists. Princeton University Press, Princeton

    Google Scholar 

  46. Greenwald, A.: The search for equilibrium in markov games. Synthesis Lectures on Artificial Intelligence and Machine Learning (2007)

    Google Scholar 

  47. Nash, J.F.: Equilibrium points in n-person games. Proceedings of the National Academy of Sciences 36, 48–49 (1950)

    Article  MATH  MathSciNet  Google Scholar 

  48. Gibbons, R.: An introduction to applicable game theory. The Journal of Economic Perspectives 11(1), 127–149 (1997)

    Google Scholar 

  49. Nwana, H.S., Lee, L., Jennings, N.R.: Co-ordination in multi-agent systems. In: Nwana, H.S., Azarmi, N. (eds.) Software Agents and Soft Computing: Towards Enhancing Machine Intelligence. LNCS, vol. 1198, pp. 42–58. Springer, Heidelberg (1997)

    Google Scholar 

  50. Chavez, A., Maes, P.K.: An agent marketplace for buying and selling goods. In: Proceedings of the First International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology, PAAM 1996 (1996)

    Google Scholar 

  51. Tsvetovatyy, M., Gini, M., Mobhasher, B., Wieckowski, Z.: MAGMA: An agent-based virtual marketplace for electronic commerce. Applied Artificial Intelligence 11(6), 501–542 (1997)

    Article  Google Scholar 

  52. Huhns, M., Singh, M.P.: CKBS-94 Tutorial: Distributed artificial intelligence for information systems, DAKE Center, University of Keele (1994)

    Google Scholar 

  53. Smith, R.G.: The contract net protocol: High-level communication and control in a distributed problem solver. IEEE Transactions on Computers 29(12), 1104–1113 (1980)

    Article  Google Scholar 

  54. O’Brien, P.D., Nicol, R.C.: FIPA-Towards a standard for software agents. BT Technology Journal 16(3), 51–59 (1998)

    Article  Google Scholar 

  55. Guestrin, C., Koller, D., Parr, R.: Multiagent planning with factored MDPs. In: Advances in Neural Information Processing Systems, vol. 14. MIT Press, Cambridge (2002)

    Google Scholar 

  56. Kuywe, L., Whiteson, S., Bakker, B., Vlassis, N.: Multiagent reinforcement learning for urban traffic control usin coordination graphs. In: Daelemans, W., Goethals, B., Morik, K. (eds.) ECML PKDD 2008, Part I. LNCS (LNAI), vol. 5211, pp. 656–671. Springer, Heidelberg (2008)

    Google Scholar 

  57. Srinivasan, D., Choy, M.C.: Neural networks for real-time traffic signal control. IEEE Trans. Intelligent Transportation Systems 7(3), 261–272 (2006)

    Article  Google Scholar 

  58. Lhotska, L.: Learning in multi-agent systems: Theoretical issues. In: Moreno-Díaz, R., Pichler, F. (eds.) EUROCAST 1997. LNCS, vol. 1333, pp. 394–405. Springer, Heidelberg (1997)

    Chapter  Google Scholar 

  59. Gomez, F., Schmidhuber, J., Miikkulainen, R.: Efficient non-linear control through neuro evolution. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 654–662. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  60. Jiu, J.: Autonomous Agents and Multi-agent Systems. World Scientific Publication, Singapore

    Google Scholar 

  61. Vassiliades, V., Cleanthous, A., Christodoulou, C.: Multiagent reinforcement learning with spiking and non-spiking agents in the iterated prisoner’s dilemma. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds.) ICANN 2009. LNCS, vol. 5768, pp. 737–746. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  62. Gabel, T., Riedmiller, M.: On a successful application of multi-agent reinforcement learning to operations research benchmarks. In: IEEE International Approximate Dynamic Programming and Reinforcement learning, pp. 68–75 (2007)

    Google Scholar 

  63. Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge

    Google Scholar 

  64. Schneider, J., Wong, W.K., Moored, A., Riedmiller, M.: Distributed Value functions. In: The Proceedings of the sixteenth International Conference on Machine Learning, pp. 371–378 (1999)

    Google Scholar 

  65. Busoniu, L., Babuska, R., De Schutter, B.: A comprehensive survey of multiagent reinforcement learning. IEEE Trans. On Systems, Man and Cybernetics Part C: Applications and Reviews 38(2), 156–212 (2008)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, National university of Singapore,  

    P. G. Balaji & D. Srinivasan

Authors
  1. P. G. Balaji
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  2. D. Srinivasan
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Editors and Affiliations

  1. Department of Electrical & Computer Engineering, National University of Singapore, 10 Kent Ridge Crescent, 119260, Singapore

    Dipti Srinivasan

  2. School of Electrical and Information Engineering, University of South Australia, Adelaide Mawson Lakes Campus, South Australia, Australia

    Lakhmi C. Jain

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Balaji, P.G., Srinivasan, D. (2010). An Introduction to Multi-Agent Systems. In: Srinivasan, D., Jain, L.C. (eds) Innovations in Multi-Agent Systems and Applications - 1. Studies in Computational Intelligence, vol 310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14435-6_1

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  • DOI: https://doi.org/10.1007/978-3-642-14435-6_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14434-9

  • Online ISBN: 978-3-642-14435-6

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