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Shrinking-Horizon Dynamic Programming
dynamic programming model predictive control revenue management
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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...
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...
Approximate Dynamic Programming via Iterated Bellman Inequalities
Convex Optimization Dynamic Programming Stochastic Control
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2015/7/9
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 ...
Quadratic Approximate Dynamic Programming for Input-Affine Systems
approximate dynamic programming stochastic control convex optimization
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2015/7/9
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...
Approximate group context tree: applications to dynamic programming and dynamic choice models
categorical time series group context tree
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2011/7/19
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.