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78
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NIPS
2001
14 years 11 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
IJCAI
2003
14 years 11 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
87
Voted
TMC
2011
219views more  TMC 2011»
14 years 4 months ago
Optimal Channel Access Management with QoS Support for Cognitive Vehicular Networks
We consider the problem of optimal channel access to provide quality of service (QoS) for data transmission in cognitive vehicular networks. In such a network the vehicular nodes ...
Dusit Niyato, Ekram Hossain, Ping Wang
ICMLA
2009
14 years 7 months ago
Sensitivity Analysis of POMDP Value Functions
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...
Stéphane Ross, Masoumeh T. Izadi, Mark Merc...
93
Voted
ATAL
2010
Springer
14 years 4 months ago
Approximate dynamic programming with affine ADDs
The Affine ADD (AADD) is an extension of the Algebraic Decision Diagram (ADD) that compactly represents context-specific, additive and multiplicative structure in functions from a...
Scott Sanner, William T. B. Uther, Karina Valdivia...