Elements of sequential decision processes

Eric V. Denardo

ResearchPublished 1966

An elucidation of the class of optimization problems that can be solved by dynamic programming techniques, and a general method for solving terminating dynamic programming problems. Problems appropriate for dynamic programming are shown to be sequential decision processes (SDPs) that pass through a set of states and whose return functions obey the monotonicity assumption that increasing the return from future states cannot decrease present returns. For every such SDP, a policy exists that is optimal for all states simultaneously; this mathematical proof has been verified for a wide range of complex problems. Algorithms previously stated by others are generalized into a technique for solving the broad class of "terminating" SDPs, which often reduces the number of alternatives requiring evaluation to computationally feasible levels.

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Denardo, Eric V., Elements of sequential decision processes. Santa Monica, CA: RAND Corporation, 1966. https://www.rand.org/pubs/research_memoranda/RM5057.html.
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