PyRL : Reinforcement Learning 

Antonin RAFFIN - Imad EL HANAFI

Understanding code 

Tools

SublimeText

Git

Libraries :

                             MatplotLib

                             TKinder

http://Gitlab.ensta.fr

Steps 

Step 1 :

Stupid agents : To understand the code

 V value agent : Incremental and Batch

 Q value agent : Incremental and Batch

Steps 

Step 2 :

2D environment  

Step 3 : 

Temporal Differencing agent 

Steps 

Step 4 :

GUI environments

Tetris simple 

Difficulties and solutions

• How to represent an environment ? Matrix or list ...
• Understand equations
• How to choose good rewards ?                      on walls, environment limit ...
• Decay rate on different environment ?

Details results and demonstrations : 

2D with walls :

Tetris

Details results and demonstrations : 

Learning curves : 

Qvalue : 2D - 20 cells 

TD : 2D - 20 cells 

Details results and demonstrations : 

Learning curves : 

TD : 2D - static walls

TD : 2D -Moving walls

Details results and demonstrations : 

Learning curves on TETRIS simple : 

TD : Tetris - 100actions - 3rows

TD : Tetris -100actions - 5rows

Details results and demonstrations : 

Learning curves on TETRIS simple : 

TD : Tetris - 100actions - 3rows

TD : Tetris -100actions - 5rows

Details results and demonstrations : 

Learning curves on TETRIS simple : 

TD : Tetris - 100actions - Bad Rewards

TD : Tetris -1000actions - 5rows

Conclusion

4 weeks project

Discovering  

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