文件列表:

MDPtoolbox (0, 2005-02-08)
MDPtoolbox\documentation (0, 2005-02-08)
MDPtoolbox\documentation\arrow.gif (231, 2005-02-08)
MDPtoolbox\documentation\DOCUMENTATION.html (3088, 2005-02-08)
MDPtoolbox\documentation\index_alphabetic.html (5173, 2005-02-08)
MDPtoolbox\documentation\index_category.html (5762, 2005-02-08)
MDPtoolbox\documentation\logo_inra.gif (11011, 2005-02-08)
MDPtoolbox\documentation\logo_mia.gif (15311, 2005-02-08)
MDPtoolbox\documentation\mdp_bellman_operator.html (3049, 2005-02-08)
MDPtoolbox\documentation\mdp_bellman_operator_policy.html (3027, 2005-02-08)
MDPtoolbox\documentation\mdp_check.html (2717, 2005-02-08)
MDPtoolbox\documentation\mdp_check_square_stochastic.html (2474, 2005-02-08)
MDPtoolbox\documentation\mdp_computePR.html (2540, 2005-02-08)
MDPtoolbox\documentation\mdp_eval_policy.html (2661, 2005-02-08)
MDPtoolbox\documentation\mdp_finite_horizon.html (3948, 2005-02-08)
MDPtoolbox\documentation\mdp_LP.html (3029, 2005-02-08)
MDPtoolbox\documentation\mdp_policy_iteration.html (4484, 2005-02-08)
MDPtoolbox\documentation\mdp_policy_iteration_modified.html (4873, 2005-02-08)
MDPtoolbox\documentation\mdp_rand.html (3374, 2005-02-08)
MDPtoolbox\documentation\mdp_relative_value_iteration.html (7526, 2005-02-08)
MDPtoolbox\documentation\mdp_span.html (2096, 2005-02-08)
MDPtoolbox\documentation\mdp_value_iteration.html (6662, 2005-02-08)
MDPtoolbox\documentation\mdp_value_iterationGS.html (9347, 2005-02-08)
MDPtoolbox\documentation\mdp_value_iteration_bound_iter.html (3427, 2005-02-08)
MDPtoolbox\documentation\mdp_verbose_silent.html (2884, 2005-02-08)
MDPtoolbox\examples (0, 2005-02-08)
MDPtoolbox\examples\race (0, 2005-02-08)
MDPtoolbox\examples\race\action_to_acceleration.m (1026, 2005-02-08)
MDPtoolbox\examples\race\compute_transitions.m (3828, 2005-02-08)
MDPtoolbox\examples\race\convert_values_to_state.m (2089, 2005-02-08)
MDPtoolbox\examples\race\data (0, 2005-02-08)
MDPtoolbox\examples\race\data\100x100 (0, 2005-02-08)
MDPtoolbox\examples\race\data\100x100\100_100_track.txt (20099, 2005-02-08)
MDPtoolbox\examples\race\data\10x10 (0, 2005-02-08)
MDPtoolbox\examples\race\data\10x10\10_10_track.txt (200, 2005-02-08)
MDPtoolbox\examples\race\data\10x10\trans_matrix_-1_-1.dat (404936, 2005-02-08)
MDPtoolbox\examples\race\data\10x10\trans_matrix_-1_0.dat (404936, 2005-02-08)
MDPtoolbox\examples\race\data\10x10\trans_matrix_-1_1.dat (404936, 2005-02-08)
MDPtoolbox\examples\race\data\10x10\trans_matrix_0_-1.dat (404936, 2005-02-08)
MDPtoolbox\examples\race\data\10x10\trans_matrix_0_0.dat (404936, 2005-02-08)
... ...

The Markov Decision Process (MDP) toolbox for MATLAB proposes functions related to the resolution of discrete-time Markov Decision Process : finite horizon, value iteration, policy iteration, linear programming algorithms with some variants. The toolbox was developped with MATLAB v6.0 by the decision team of the Biometry and Artificial Intelligence Unit of INRA Toulouse (France). See for more information. NOTATION states: set of {1, 2, ..., S} actions: set of {1, 2, ..., A} transition matrix P: P(s,s',a)is the probability to be in state s' when system in state s and action a performed by decision maker reward function R and PR: R(s,s',a) is the reward when system is in state s at decision epoch t and is in state s' at decision epoch t+1, with action a performed by decision maker; PR(s,a): is the reward when system is in state s at decision epoch t and action a performed by decision maker The HTML toolbox documentation describing the use of the m-functions can be visualized with MATLAB navigator (used for MATLAB help). In the 'File' menu, choose the 'Open' item. Open the sub-directory documentation. Select the item 'All Files (*.*)' for the attribut 'Files of type'. Then select the file DOCUMENTATION.html and open it. The directory mdp_toolbox/documentation contains all the pages describing in HTML the m-functions. The initial version 1.0 was released on July 31, 2001. The actual version 2.0 was released on February 4, 2005. It handles sparse matrices and contains an example.

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