Multiagent collaborative learning for distributed business systems

Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004

Volumn 3, Issue , 2004, Pages 1156-1163

  Guo, Yutao ^a   Müller, Jörg P ^a  

^a SIEMENS AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPETITION; COMPUTER ARCHITECTURE; DATA ACQUISITION; DECISION SUPPORT SYSTEMS; DISTRIBUTED COMPUTER SYSTEMS; EMBEDDED SYSTEMS; SOCIETIES AND INSTITUTIONS;

COLLABORATIVE LEARNING; DISTRIBUTED BUSINESS SYSTEMS; MULTIAGENT ARCHITECTURES; SUPPLY CHAIN;

MULTI AGENT SYSTEMS;

EID: 4544342441     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. R. Chen, K. Sivakumar, and H. Kargupta. Collective mining of bayesian networks from distributed heterogeneous data. Knowledge and Information Systems, 6(2), 2004.
2. T. G. Dietterich. Machine-learning research: Four current directions. The AI Magazine, 18(4):97-136, 1998.
3. K. Fischer, J. P. Müller, and M. Pischel. Cooperative transportation scheduling: an application domain for DAI Journal of Applied Artificial Intelligence, 10(1), 1996.
4. D. Frey, T. Stockheim, P.-O. Woelk, and R. Zimmermann. Integrated multi-agent-based supply chain management. In Proceedings of the 12th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE-2003), pages 24-29. IEEE, 2003.
5. Y. Guo, J. Müller, and B. Bauer. A multiagent approach for logistics performance prediction using historical and context information. In Proceedings of The Third International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS'04), New York, 2004. IEEE Press.
6. N. R. Jennings, P. Faratin, T. J. Norman, P. O'Brien, M. E. Wiegand, C. Voudouris, J. L. Alty, T. Miah, and E. H. Mamdani. ADEPT: Managing business processes using intelligent agents. In Proceedings of the 16th Annual Conference of the British Computer Society Specialist Group on Expert Systems (ISIP Track), pages 5-23, Cambridge, UK, 1996.
7. N. R. Jennings, K. Sycara, and M. Wooldridge. A roadmap of agent research and development. Journal of Autonomous Agents and Multi-Agent Systems, 1(1):7-38, 1998.
8. P. Langley, W. Iba, and K. Thompson. An analysis of bayesian classifiers. In Proceedings of the Tenth National Conference on Artificial Intelligence, pages 399-406. AAAI Press, 1992.
9. P. Langley and S. Sage. Induction of selective bayesian classifiers. In Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, pages 399-406. Morgan Kaufmann, 1994.
10. P. J. Modi and W.-M. Shen. Collaborative multiagent learning for classification tasks. In Proceedings of the Fifth International Conference on Autonomous Agents, pages 37-38, Montreal, 2001. ACM Press.
11. J. P. Müller, B. Bauer, and M. Berger. Software Agents for Electronic Business: Opportunities and Challenges, volume 2322 of Lecture Notes in Computer Science, pages 61-106. Springer, 2002.
12. B.-H. Park and H. Kargupta. Distributed data mining: Algorithms, systems, and applications. In N. Ye, editor, The Handbook of Data Mining. Lawrence Erlbaum, 2003.
13. A. Prodromidis and P. Chan. Meta-learning in distributed data mining systems: Issues and approaches, 2000.
14. T. Sandholm. An implementation of the contract net protocol based on marginal-cost calculations. In Proc. 11th National Conference on Artificial Intelligence (AAAI-93), pages 256-262, 1993.
15. C. E. Shannon. A mathematical theory of communication. Bell Systems Technology Journal, 27(1,3):379-423 and 623-656, July and October 1948.
16. V. Vapnik. The Nature of Statistical Learning Theory. Springer-Verlag, New York, 1995.
17. X. Wang and T. Sandholm. Reinforcement learning to play an optimal nash equilibrium in team markov games. In Proceedings of the 16th Neural Information Processing Systems: Natural and Synthetic (NIPS) conference, Vancouver, 2002.
18. D. Wettschereck, D. W. Aha, and T. Mohri. A review and empirical evaluation of feature weighting methods for a class of lazy learning algorithms. Artificial Intelligence Review, 11:273-314, July and Oct. 1997.
19. D. Wolpert. Stacked generalization. Neural Networks, 5:241-259, 1992.
20. Z. Zheng. Naive bayesian classifier committees. In Proceedings of the Tenth European Conference on Machine Learning, pages 196-207. Springet-Verlag, 1998.