Abstract
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.
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