1. The main problem in the dynamical decision-making process is to determine how to update the information and to apply a control action in order to reach ...
Using stochastic filtering theory, Markovian evolution can be modelled in terms of latent variables, which naturally leads to high-dimensional state space, ...
Stochastic Switching for Partially Observable. Dynamics and Optimal Asset Allocation ... A survey of partially observable Markov de ision pro esses: Theory ...
Using stochastic filtering theory, Markovian evolution can be modeled in terms of latent variables, which naturally leads to high dimensional state space, ...
Stochastic Switching for Partially Observable Dynamics and Optimal ...
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Juri Hinz, 2015. "Stochastic Switching for Partially Observable Dynamics and Optimal Asset Allocation," Research Paper Series 358, Quantitative Finance Research ...
Stochastic switching for partially observable dynamics and optimal asset allocation. J Hinz, J Yee. International Journal of Control 90 (3), 553-565, 2017. 10 ...
This paper will describe the implementation of fast and accurate algorithms to address problems with a finite time setting, finite action set, and convex reward ...
Stochastic switching for partially observable dynamics and optimal asset allocation. International Journal of Control, Vol. 90, No. 3 | 15 June 2016. Using ...
J. Hinz, J. Yee, “Stochastic switching for partially observable dynamics and optimal asset allocation”, Int. J. Control, 90:3 (2017), 553–565 crossref ...
This paper surveys models and algorithms dealing with partially observable Markov decision processes.