Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/322860 
Year of Publication: 
2011
Series/Report no.: 
Discussion Papers Series No. 11-18
Publisher: 
Utrecht University, Utrecht School of Economics, Tjalling C. Koopmans Research Institute, Utrecht
Abstract: 
In this paper we derive the closed loop form of the Expected Optimal Feedback rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (1981,2002, Chapter 6) where parameters are assumed to vary randomly around a known constant mean. Furthermore, we show that the cautionary myopic rule in Beck and Wieland (2002) model, a test bed for comparing various stochastic optimizations approaches, can be cast into this framework and can be treated as a special case of this solution.
Subjects: 
Optimal experimentation
stochastic optimization
time-varying parameters
expected optimal feedback
Document Type: 
Working Paper

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