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EUROGP
2006
Springer
140views Optimization» more  EUROGP 2006»
14 years 1 months ago
Evolving Noisy Oscillatory Dynamics in Genetic Regulatory Networks
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation...
André Leier, P. Dwight Kuo, Wolfgang Banzha...
ICASSP
2011
IEEE
13 years 1 months ago
Convergence of a distributed parameter estimator for sensor networks with local averaging of the estimates
The paper addresses the convergence of a decentralized Robbins-Monro algorithm for networks of agents. This algorithm combines local stochastic approximation steps for finding th...
Pascal Bianchi, Gersende Fort, Walid Hachem, J&eac...
AIPS
1998
13 years 11 months ago
Solving Stochastic Planning Problems with Large State and Action Spaces
Planning methods for deterministic planning problems traditionally exploit factored representations to encode the dynamics of problems in terms of a set of parameters, e.g., the l...
Thomas Dean, Robert Givan, Kee-Eung Kim
COMCOM
2004
145views more  COMCOM 2004»
13 years 9 months ago
Framework based on stochastic L-Systems for modeling IP traffic with multifractal behavior
In a previous work we have introduced a multifractal traffic model based on so-called stochastic L-Systems, which were introduced by biologist A. Lindenmayer as a method to model ...
Paulo Salvador, António Nogueira, Rui T. Va...
SIAMCO
2002
71views more  SIAMCO 2002»
13 years 9 months ago
Rate of Convergence for Constrained Stochastic Approximation Algorithms
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
Robert Buche, Harold J. Kushner