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Complex decisions made simple: a primer on stochastic dynamic programming
Author(s) -
Marescot Lucile,
Chapron Guillaume,
Chadès Iadine,
Fackler Paul L.,
Duchamp Christophe,
Marboutin Eric,
Gimenez Olivier
Publication year - 2013
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12082
Subject(s) - dynamic programming , stochastic programming , computer science , simple (philosophy) , population , mathematical optimization , management science , ecology , operations research , mathematics , economics , algorithm , biology , philosophy , epistemology , sociology , demography
Summary Under increasing environmental and financial constraints, ecologists are faced with making decisions about dynamic and uncertain biological systems. To do so, stochastic dynamic programming ( SDP ) is the most relevant tool for determining an optimal sequence of decisions over time. Despite an increasing number of applications in ecology, SDP still suffers from a lack of widespread understanding. The required mathematical and programming knowledge as well as the absence of introductory material provide plausible explanations for this. Here, we fill this gap by explaining the main concepts of SDP and providing useful guidelines to implement this technique, including R code. We illustrate each step of SDP required to derive an optimal strategy using a wildlife management problem of the French wolf population. Stochastic dynamic programming is a powerful technique to make decisions in presence of uncertainty about biological stochastic systems changing through time. We hope this review will provide an entry point into the technical literature about SDP and will improve its application in ecology.