Learn R Programming

MDPtoolbox (version 4.0.2)

Markov Decision Processes toolbox

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.

Copy Link

Version

Install

install.packages('MDPtoolbox')

Monthly Downloads

630

Version

4.0.2

License

BSD_3_clause + file LICENSE

Maintainer

Guillaume Chapron

Last Published

July 21st, 2014

Functions in MDPtoolbox (4.0.2)

mdp_example_forest

Generates a MDP for a simple forest management problem
mdp_computePR

Computes a reward matrix for any form of transition and reward functions
mdp_check_square_stochastic

Checks if a matrix is square and stochastic
mdp_span

Evaluates the span of a vector
mdp_computePpolicyPRpolicy

Computes the transition matrix and the reward matrix for a fixed policy
mdp_bellman_operator

Applies the Bellman operator
MDPtoolbox-package

Markov Decision Processes toolbox
mdp_check

Checks the validity of a MDP