Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/135214
Title: ALGORITHMS FOR CONVEX SWITCHING SYSTEMS
Authors: LI SHANGRU
Keywords: convex switching, Markov decision, subgradient envelope, matrix representative, POMDP, duality bounds,
Issue Date: 30-Sep-2016
Source: LI SHANGRU (2016-09-30). ALGORITHMS FOR CONVEX SWITCHING SYSTEMS. ScholarBank@NUS Repository.
Abstract: In this thesis we introduce the convex switching system, a specific structured model in Markov decision theory. The main feature is that it contains convex reward functions and the underlying states follow linear dynamics. Many problems in engineering, finance and statistics can be modelled under the scheme of convex switching systems. Mathematically, an exact solution for such problems can be difficult sometimes, especially when the dimension of states is high. Here in this thesis we introduce an approximate algorithm for the convex switching problems. It is also shown that the algorithms can be applicable for problems with non-convex rewards and POMDPs/HMMs with nonlinear dynamics. Some numerical illustrations and simulations in real-life problems are shown.
URI: http://scholarbank.nus.edu.sg/handle/10635/135214
Appears in Collections:Master's Theses (Open)

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