Sciweavers

4 search results - page 1 / 1
» Recursive Markov Chains, Stochastic Grammars, and Monotone S...
Sort
View
STACS
2005
Springer
13 years 10 months ago
Recursive Markov Chains, Stochastic Grammars, and Monotone Systems of Nonlinear Equations
We introduce and study Recursive Markov Chains (RMCs), which extend ordinary finite state Markov chains with the ability to invoke other Markov chains in a potentially recursive m...
Kousha Etessami, Mihalis Yannakakis
STOC
2007
ACM
132views Algorithms» more  STOC 2007»
14 years 5 months ago
On the convergence of Newton's method for monotone systems of polynomial equations
Monotone systems of polynomial equations (MSPEs) are systems of fixed-point equations X1 = f1(X1, . . . , Xn), . . . , Xn = fn(X1, . . . , Xn) where each fi is a polynomial with p...
Stefan Kiefer, Michael Luttenberger, Javier Esparz...
CDC
2010
IEEE
167views Control Systems» more  CDC 2010»
12 years 11 months ago
Numerical methods for the optimization of nonlinear stochastic delay systems, and an application to internet regulation
The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...
Harold J. Kushner
CDC
2009
IEEE
132views Control Systems» more  CDC 2009»
13 years 9 months ago
Q-learning and Pontryagin's Minimum Principle
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
Prashant G. Mehta, Sean P. Meyn