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Shrinking-Horizon Dynamic Programming     dynamic programming  model predictive control  revenue management       font style='font-size:12px;'> 2015/7/9
We describe a heuristic control policy, for a general finite-horizon stochastic control problem, that can be used when the current process disturbance is not conditionally independent of previous dist...
Min-Max Approximate Dynamic Programming     Min-Max Approximate Dynamic Programming       font style='font-size:12px;'> 2015/7/9
In this paper we describe an approximate dynamic programming policy for a discrete-time dynamical system perturbed by noise. The approximate value function is the pointwise supremum of a family of low...
In this paper we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based ...
We consider the use of quadratic approximate value functions for stochastic control problems with input-affine dynamics and convex stage cost and constraints. Evaluating the approximate dynamic progra...
The paper considers a variable length Markov chain model associated with a group of stationary processes that share the same context tree but potentially different conditional probabilities.

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