Deriving a near-optimal power management policy using model-free reinforcement learning and Bayesian classification

Proceedings - Design Automation Conference

Volumn , Issue , 2011, Pages 41-46

  Wang, Yanzhi ^a   Xie, Qing ^a   Ammari, Ahmed ^b   Pedram, Massoud ^a  

^a University of Southern California ^*  (United States)

^b UNIVERSITY OF CARTHAGE   (Tunisia)

Author keywords

Bayes Classification; Dynamic Power Management; Reinforcement Learning

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; COMPUTER AIDED DESIGN; DYNAMICAL SYSTEMS; MACHINE LEARNING; MARKOV PROCESSES; ONLINE SYSTEMS; POWER MANAGEMENT; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

BAYES CLASSIFICATION; BAYESIAN CLASSIFICATION; DYNAMIC POWER MANAGEMENT; LATENCY REDUCTION; SEMI-MARKOV DECISION PROCESS; STOCHASTIC DYNAMICAL SYSTEM; TEMPORAL DIFFERENCE LEARNING; USER-DEFINED PARAMETERS;

REINFORCEMENT LEARNING;

EID: 80052684654     PISSN: 0738100X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2024724.2024735     Document Type: Conference Paper

References (14)

1. L. Benini, A. Bogliolo and G. De Micheli, "A survey of design techniques for system level dynamic power management," IEEE Trans. on VLSI Systems, Vol. 8, Issue 3, pp. 299-316, 2000.
2. M. Srivastava, A. Chandrakasan and R. Brodersen, "Predictive system shutdown and other architectural techniques for energy efficient programmable computation," IEEE Trans. on VLSI, 1996.
3. C. H. Hwang and A. C. Wu, "A predictive system shutdown method for energy saving of event-driven computation," in ICCAD '97.
4. L. Benini, G. Paleologo, A. Bogliolo and G. De Micheli, "Policy optimization for dynamic power management," IEEE Trans. on CAD, Vol. 18, pp. 813-833, Jun. 1999.
5. Q. Qiu and M. Pedram, "Dynamic Power Management Based on Continuous-Time Markov Decision Processes," in DAC '99.
6. T. Simunic, L. Benini, P. Glynn and G. De Micheli, "Event-driven power management," IEEE Trans. on CAD, 2001.
7. H. Jung and M. Pedram, "Dynamic power management under uncertain information," in DATE '07, pp. 1060-1065, Apr. 2007.
8. Q. Qiu, Y. Tan and Q. Wu, "Stochastic Modeling and Optimization for Robust Power Management in a Partially Observable System," in DATE '07, pp. 779-784, Apr. 2007.
9. G. Dhiman and T. Simunic Rosing, "Dynamic power management using machine learning," in ICCAD '06, pp. 747-754, Nov. 2006.
10. Y. Tan, W. Liu and Q. Qiu, "Adaptive power management using reinforcement learning," in ICCAD '09, pp. 461-467, Nov. 2009.
11. S. Bradtke and M. Duff, "Reinforcement learning methods for continuous-time Markov decision problems," in Advances in Neural Information Processing Systems 7, pp. 393-400, MIT Press, 1995.
12. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, MIT Press, Cambridge, MA, 1998.
13. C. Watkins, Learning from Delayed Rewards, PhD thesis, Cambridge University, Cambridge, England, 1989.
14. C. M. Bishop, Pattern Recognition and Machine Learning, Springer, August 2006.