An Optimizer's Approach to Stochastic Control Problems With Nonclassical Information Structures
DSpace at IIT Bombay
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Title |
An Optimizer's Approach to Stochastic Control Problems With Nonclassical Information Structures
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Creator |
KULKARNI, AA
COLEMAN, TP |
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Subject |
SYSTEMS
DESIGN TEAMS Optimal control stochastic systems optimization information theory decentralized control networked control systems |
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Description |
We present a general optimization-based framework for stochastic control problems with nonclassical information structures. We cast these problems equivalently as optimization problems on joint distributions. The resulting problems are necessarily nonconvex. Our approach to solving them is through convex relaxation. We solve the instance solved by Bansal and Basar ("Stochastic teams with nonclassical information revisited: When is an affine law optimal?", IEEE Trans. Automatic Control, 1987) with a particular application of this approach that uses the data processing inequality for constructing the convex relaxation. Using certain f-divergences, we obtain a new, larger set of inverse optimal cost functions for such problems. Insights are obtained on the relation between the structure of cost functions and of convex relaxations for inverse optimal control.
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Publisher |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Date |
2016-01-15T09:06:36Z
2016-01-15T09:06:36Z 2015 |
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Type |
Article
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Identifier |
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 60(4)937-949
0018-9286 1558-2523 http://dx.doi.org/10.1109/TAC.2014.2362596 http://dspace.library.iitb.ac.in/jspui/handle/100/18233 |
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Language |
en
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