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MDPtoolbox
View on CRAN: Click
here
Download and install MDPtoolbox package within the R console
Install from CRAN:
install.packages("MDPtoolbox")
Install from Github:
library("remotes")
install_github("cran/MDPtoolbox") Install by package version:
library("remotes")
install_version("MDPtoolbox", "4.0.3") Attach the package and use:
library("MDPtoolbox")
Maintained by
Guillaume Chapron
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-12-11
Latest Update: 2017-03-03
Description:
The Markov Decision Processes (MDP) toolbox proposes functions related to the resolution of discrete-time Markov Decision Processes: finite horizon, value iteration, policy iteration, linear programming algorithms with some variants and also proposes some functions related to Reinforcement Learning.
How to cite:
Guillaume Chapron (2012). MDPtoolbox: Markov Decision Processes Toolbox. R package version 4.0.3, https://cran.r-project.org/web/packages/MDPtoolbox. Accessed 23 Aug. 2026.
Previous versions and publish date:
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Other R packages that MDPtoolbox depends,
imports, suggests or enhances
Complete documentation for MDPtoolbox
Functions, R codes and Examples using
the MDPtoolbox R package
Some associated functions: MDPtoolbox-package . mdp_LP . mdp_Q_learning . mdp_bellman_operator . mdp_check . mdp_check_square_stochastic . mdp_computePR . mdp_computePpolicyPRpolicy . mdp_eval_policy_TD_0 . mdp_eval_policy_iterative . mdp_eval_policy_matrix . mdp_eval_policy_optimality . mdp_example_forest . mdp_example_rand . mdp_finite_horizon . mdp_policy_iteration . mdp_policy_iteration_modified . mdp_relative_value_iteration . mdp_span . mdp_value_iteration . mdp_value_iterationGS . mdp_value_iteration_bound_iter .
Some associated R codes: Full MDPtoolbox package functions and examples
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