Assessing usage patterns to improve data allocation via auctions

Proceedings - 4th International Conference on MultiAgent Systems, ICMAS 2000

Volumn , Issue , 2000, Pages 47-54

  Azoulay Schwart, R ^a   Kraus, S ^a,b  

^a BAR ILAN UNIVERSITY   (Israel)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMMERCE; LEARNING SYSTEMS; NEAREST NEIGHBOR SEARCH;

BIDDING MECHANISM; DATA ALLOCATION; DATA ALLOCATION PROBLEMS; INCOMPLETE INFORMATION; K-NEAREST NEIGHBORS; LEARNING METHODS; LEARNING PROCESS; USAGE PATTERNS;

MULTI AGENT SYSTEMS;

EID: 84962110858     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMAS.2000.858430     Document Type: Conference Paper

References (21)

1. E. B. Baum and D. Haussler. What size net gives valid generalization? Neural Computation, 1:151-160, 1989.
2. C. Boutilier, M. Goldszmidt, and B. Sabata. Sequential auctions for the allocation of resources with complementarities. In Proc. of IJCAI99, Sweden, 1999.
3. T. E. Copeland and J. F. Weston. Financial Theory and Corporate Policy. Addison-Wesley Publishing Company, 1992.
4. K. Decker and K. Sycara. Intelligent adaptive information agents. Information Systems, 9:239-260, 1997.
5. J.L.Devore. Probability and Statistics for Engineering and Sciences. Brooks/Cole Publishing Comp., California, 1991.
6. X. Du and F. J. Maryanski. Data allocation in a dynamically reconfigurable environment. In Proc. of the IEEE Fourth Int. Conf. Data Engineering, pages 74-81, Los Angeles, 1988.
7. E. Ephrati and J. S. Rosenschein. The Clarke tax as a consensus mechanism among automated agents. In Proc. of AAAI-91, pages 173-178, California, 1991.
8. D. Fudenberg and J. Tirole. Game Theory. MIT Press, 1991.
9. B. Huberman and S. H. Clearwater. A multi-agent system for controlling building environments. In Proceedings of ICMAS-95, pages 171-176, San Fransisco, 1995.
10. L. P. Kaelbling and A. W. Moore. Reinforcement learning: A survey. JAIR, 4:237-285, 1996.
11. K. Mehrotra, C. K. Mohan, and S. Ranka. Elements of Artificial Neural Networks. MIT Press, 1997.
12. T. M. Mitchell. Machine Learning. McGraw-Hill, 1997.
13. NASA. EOSDIS-Home-Page. http://spsosun.gsfc.nasa.gov/New-EOSDIS.html.
14. T. W. Sandholm. Limitations of the Vickrey Auction in Computational Multiagent Systems. In proc. of ICMAS-96, pages 299-306, Japan, 1996.
15. A. Schaerf, Y. Shoham, and M. Tennenholtz. Adaptive load balancing: A study in multi-agent learning. JAIR, 2:475-500, 1995.
16. R. Schwartz and S. Kraus. Bidding mechanisms for data allocation in multi-agent environments. In M. P. Singh, A. S. Rao, and M. J. Wooldridge, editors, Intelligent Agents IV, LNAI, volume 1365, pages 61-75. Springer-Verlag, 1998.
17. J. Tirole. The Theory of Industrial Organization. MIT press, 1988.
18. W. Vickrey. Counterspeculation, auctions, and competitive sealed tenders. J. of Finance, 16:8-37, 1961.
19. W. E. Walsh, M. P. Wellman, P. R. Wurman, and J. K. M. Mason. Some economics of market-based distributed scheduling. In Proc. of ICDCS-98, Amsterdam, 1998.
20. S. M. Weiss and N. Indurkhya. Rule-based machine learning methods for functional prediction. JAIR, 2:383-403, 1995.
21. P. R. Wurman, W. E. Walsh, and M. P. Wellman. Flexible double auctions for electronic commerce: Theory and implementation. Decision Support Systems, 24:17-27, 1998.