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ITJ Autonomic Computing
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Autonomic Computing
Volume 10    Issue 04    Published November 9, 2006
ISSN 1535-864X    DOI: 10.1535/itj.1004.05

  Section 8 of 9  
Machine learning for Adaptive Power Management
References

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[2] Bertsekas, D.P., "Dynamic Programming and Optimal Control," Athena Scientific, 3rd edition, 2005.

[3] Billings, D., Papp, D., Schaeffer, J., and Szafron, D., "Opponent Modeling in Poker," in Proceedings of the Fifteenth National Conference on Artificial Intelligence, pp. 493–499, 1998.

[4] Carmel, D. and Markovitch, S., "Incorporating Opponent Models into Adversary Search," in Proceedings of the Thirteenth National Conference on Artificial Intelligence, pp. 120–125, 1996.

[5] Duda, R. O., Hart, P. E., and Stork, D. G., Pattern Classification (2nd ed.), New York: John Wiley & Sons, Inc., 2001.

[6] Duong, T., Bui, H., Phung, D., and Venkatesh S., "Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model," International Conference on Computer Vision & Pattern Recognition, 2005.

[7] Hwang, C. H. and Wu, A., "A Predictive System Shutdown Method for Energy Saving of Event-Driven Computation," in Proceedings of the International Conference on Computer Aided Design, Morgan Kaufmann, San Francisco, CA, pp. 28–32, 1997.

[8] Kaelbling, L. P., Littman, M. L. and Cassandara A. R., "Planning and Acting in Partially Observable Stochastic Domains," Artificial Intelligence, 101, pp. 99–134, 1998.

[9] Littman, M., Nguyen, T., Hirsh, H., Fenson, E. M., and Howard, R., "Cost-Sensitive Fault Remediation for Autonomic Computing," International Joint Conference on Artificial Intelligence, 2003.

[10] Madani, O., Hanks, S., and Gordon, A., "On the Undecidability of Probabilistic Planning and Infinite Horizon Partially Observable Markov Decision Processes," in Proceedings of the Seventeenth National Conference in Artificial Intelligence, pp. 409–416 1999.

[11] Papadimitriou, C. and Tsitsiklis, J.,"The Complexity of Markov Decision Processes," Mathematics of Operation Research, Vol. 12, Issue 3, 1987.

[12] Ren, Z. and Krogh, B.H., "Hierarchical Adaptive Dynamic Power Management," IEEE Transactions on Computer, Vol. 54, Issue 4, pp. 409–420, 2005.

[13] Shani, G., Brafman, R., and Heckerman, D. "An MDP-based recommender system," in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence, pp. 453–460, 2002.

[14] Simunic, T., Benini, L., Glynn, P., and De Micheli, G., "Event-Driven Power Management," IEEE Transactions on CAD, Vol. 20, Issue 21, pp. 840–857, 2001.

[15] Simunic, T., "Dynamic Management of Power Consumption," in R. Graybill and R. Melhem, editors, Power Aware Computing, Chapter 6, Kluwer Academic, 2002.

[16] Srivastava, M., Chandrakasan, A., and Brodersen, R., "Predictive System Shutdown and Other Energy Efficient Programmable Computation," IEEE Transaction on VLSI Systems, Vol. 4, Issue 1, pp. 42–55, 1996.


  Section 8 of 9  

In this article
Abstract
Introduction
Adaptive Power Management
The direct approach
Discussion
Conclusion
Acknowledgments
References
Authors' biographies
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