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CDC
2010
IEEE
105views Control Systems» more  CDC 2010»
13 years 2 months ago
Learning in mean-field oscillator games
This research concerns a noncooperative dynamic game with large number of oscillators. The states are interpreted as the phase angles for a collection of non-homogeneous oscillator...
Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday...
ML
1998
ACM
101views Machine Learning» more  ML 1998»
13 years 7 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto
INFOCOM
2006
IEEE
14 years 1 months ago
Sampling Techniques for Large, Dynamic Graphs
— Peer-to-peer systems are becoming increasingly popular, with millions of simultaneous users and a wide range of applications. Understanding existing systems and devising new pe...
Daniel Stutzbach, Reza Rejaie, Nick G. Duffield, S...
WWW
2009
ACM
14 years 8 months ago
Personalized recommendation on dynamic content using predictive bilinear models
In Web-based services of dynamic content (such as news articles), recommender systems face the difficulty of timely identifying new items of high-quality and providing recommendat...
Wei Chu, Seung-Taek Park
IDA
1999
Springer
13 years 11 months ago
Reasoning about Input-Output Modeling of Dynamical Systems
The goal of input-output modeling is to apply a test input to a system, analyze the results, and learn something useful from the causeeffect pair. Any automated modeling tool that...
Matthew Easley, Elizabeth Bradley