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» Multi-Agent Learning with Policy Prediction
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COLT
2000
Springer
13 years 9 months ago
Bias-Variance Error Bounds for Temporal Difference Updates
We give the first rigorous upper bounds on the error of temporal difference (td) algorithms for policy evaluation as a function of the amount of experience. These upper bounds pr...
Michael J. Kearns, Satinder P. Singh
EENERGY
2010
13 years 9 months ago
Towards energy-aware scheduling in data centers using machine learning
As energy-related costs have become a major economical factor for IT infrastructures and data-centers, companies and the research community are being challenged to find better an...
Josep Lluis Berral, Iñigo Goiri, Ramon Nou,...
ICML
2004
IEEE
14 years 6 months ago
Utile distinction hidden Markov models
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
Daan Wierstra, Marco Wiering
CEC
2007
IEEE
13 years 9 months ago
Adaptive farming strategies for dynamic economic environment
This paper aims to forecast the economic impacts of changing land-use in UK uplands. We assume that farmers adaptively learn and respond to a dynamic economic environment. The main...
Nanlin Jin, Mette Termansen, Klaus Hubacek, Joseph...
JSSPP
2007
Springer
13 years 11 months ago
A Self-optimized Job Scheduler for Heterogeneous Server Clusters
Heterogeneous clusters and grid infrastructures are becoming increasingly popular. In these computing infrastructures, machines have different resources, including memory sizes, d...
Elad Yom-Tov, Yariv Aridor