248 search results - page 27 / 50 » Rate of Convergence for Constrained Stochastic Approximation... |
146
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NIPS
2008
15 years 5 months ago
2008
In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
160
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INFOCOM
2007
IEEE
15 years 10 months ago
2007
IEEE
— This paper studies the tradeoff between energy consumption and application performance in wireless sensor networks by investigating the interaction between network lifetime max...
130
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NIPS
2008
15 years 5 months ago
2008
Most algorithms for solving Markov decision processes rely on a discount factor, which ensures their convergence. It is generally assumed that using an artificially low discount f...
130
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IAT
2006
IEEE
15 years 10 months ago
2006
IEEE
The Distributed Probabilistic Protocol (DPP) is a new, approximate algorithm for solving Distributed Constraint Satisfaction Problems (DCSPs) that exploits prior knowledge to impr...
163
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MOC
2010
14 years 10 months ago
2010
We study H(div) preconditioning for the saddle-point systems that arise in a stochastic Galerkin mixed formulation of the steady-state diffusion problem with random data. The key i...