Metadata-Version: 2.1
Name: md_pro
Version: 0.0.13
Summary: Markov Decision Process
Home-page: https://github.com/ga74kud/mdp
Author: Michael Hartmann
Author-email: michael.hartmann@v2c2.at
License: GNU GENERAL PUBLIC LICENSE
Description: ![](/images/pexels-skitterphoto-1083355.jpg)
        
        
        # Markov Decision Process
        Markov Decision Process
        
        - [x] Markov Decision Process
        
        # Installation
        ```bash
        pip install md-pro
        ```
        
        # Usage
        
        ```python
            ##################
            ### Parameters ###
            ##################
            parser = argparse.ArgumentParser()
            parser.add_argument('--sample_time', '-Ts', type=float, help='Ts=0.1',
                                default='0.1', required=False)
            parser.add_argument('--gamma', '-gam', type=float, help='gamma=0.9',
                                default='0.9', required=False)
            parser.add_argument('--x_grid', '-xgr', type=int, help='x_grid=5',
                                default='8', required=False)
            parser.add_argument('--y_grid', '-ygr', type=int, help='y_grid=5',
                                default='5', required=False)
            parser.add_argument('--n_optimal', '-nopt', type=int, help='n_optimal=5',
                                default='5', required=False)
            args = parser.parse_args()
            params = vars(args)
            ####################################################
            ### Challenge with Markov Decision Process (MDP) ###
            ####################################################
            #start point
            strt_pnt='0'
            # points
            P=get_meshgrid_points(params)
            # Topology
            T, S = get_simple_topology_for_regular_grid(params, P)
            # rewards
            R = {'35': 100}
            mdp_challenge = {'S': S, 'R': R, 'T': T, 'P': P}
        
            dict_mdp=start_mdp(params, mdp_challenge)
            reach_set=reach_n_steps(strt_pnt, mdp_challenge, dict_mdp, params, steps=8)
            optimal_traj=get_trajectory(strt_pnt, dict_mdp, reach_set)
            plot_the_result(dict_mdp, mdp_challenge)
        ```
        
        
        ... should produce:
        
        ![](/images/grid_mdp.png)
        
        
        # Citation
        
        Please cite following document if you use this python package:
        ```
        TODO
        ```
        
        
        Image source: https://www.pexels.com/photo/photo-of-black-and-beige-wooden-chess-pieces-with-white-background-1083355/
Platform: UNKNOWN
Description-Content-Type: text/markdown
