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ICML
1996
IEEE
15 years 1 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
65
Voted
EOR
2006
66views more  EOR 2006»
14 years 9 months ago
Performance prediction of an unmanned airborne vehicle multi-agent system
Consider unmanned airborne vehicle (UAV) control agents in a dynamic multi-agent system. The agents must have a set of goals such as destination airport and intermediate positions...
Zhaotong Lian, Abhijit Deshmukh
ISCA
2009
IEEE
318views Hardware» more  ISCA 2009»
15 years 4 months ago
Thread criticality predictors for dynamic performance, power, and resource management in chip multiprocessors
With the shift towards chip multiprocessors (CMPs), exploiting and managing parallelism has become a central problem in computer systems. Many issues of parallelism management boi...
Abhishek Bhattacharjee, Margaret Martonosi
SAC
2010
ACM
15 years 4 months ago
MetaSelf: an architecture and a development method for dependable self-* systems
This paper proposes a software architecture and a development process for engineering dependable and controllable self-organising (SO) systems. Our approach addresses dependabilit...
Giovanna Di Marzo Serugendo, John S. Fitzgerald, A...
ICML
2007
IEEE
15 years 10 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...