Open AccessMDPtoolbox: a multi‐platform toolbox to solve stochastic dynamic programming problems
Author(s) -
Chadès Iadine,
Chapron Guillaume,
Cros MarieJosée,
Garcia Frédérick,
Sabbadin Régis
Publication year - 2014
Publication title -
ecography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.973
H-Index - 128
eISSN - 1600-0587
pISSN - 0906-7590
DOI - 10.1111/ecog.00888
Subject(s) - toolbox , computer science , markov decision process , dynamic programming , mathematical optimization , set (abstract data type) , stochastic programming , range (aeronautics) , markov chain , matlab , markov process , operations research , machine learning , algorithm , programming language , mathematics , engineering , aerospace engineering , statistics
Stochastic dynamic programming (SDP) or Markov decision processes (MDP) are increasingly being used in ecology to find the best decisions over time and under uncertainty so that the chance of achieving an objective is maximised. To date, few programs are available to solve SDP/MDP. We present MDPtoolbox, a multi‐platform set of functions to solve Markov decision problems (MATLAB, GNU Octave, Scilab and R). MDPtoolbox provides state‐of‐the‐art and ready to use algorithms to solve a wide range of MDPs. MDPtoolbox is easy to use, freely available and has been continuously improved since 2004. We illustrate how to use MDPtoolbox on a dynamic reserve design problem.