The value of (bounded) memory in a changing world
Daniel Monte () and
Maher Said ()
Economic Theory, 2014, vol. 56, issue 1, 59-82
This paper explores the value of memory in decision making in dynamic environments. We examine the decision problem faced by an agent with bounded memory who receives a sequence of signals from a partially observable Markov decision process. We characterize environments in which the optimal memory consists of only two states. In addition, we show that the marginal value of additional memory states need not be positive and may even be negative in the absence of free disposal. Copyright Springer-Verlag Berlin Heidelberg 2014
Keywords: Bounded memory; Dynamic decision making; Partially observable Markov decision process; C61; D81; D83 (search for similar items in EconPapers)
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Working Paper: Learning in hidden Markov models with bounded memory (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:spr:joecth:v:56:y:2014:i:1:p:59-82
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