@@ -9,6 +9,12 @@ In the links below you find introductions to training an agent on Flatland:
...
@@ -9,6 +9,12 @@ In the links below you find introductions to training an agent on Flatland:
- Training multiple agents to avoid conflicts ([Introduction](https://gitlab.aicrowd.com/flatland/baselines/blob/master/torch_training/Multi_Agent_Training_Intro.md))
- Training multiple agents to avoid conflicts ([Introduction](https://gitlab.aicrowd.com/flatland/baselines/blob/master/torch_training/Multi_Agent_Training_Intro.md))
Use this introductions to get used to the Flatland environment. Then build your own predictors, observations and agents to improve the performance even more and solve the most complex environments of the challenge.
Use this introductions to get used to the Flatland environment. Then build your own predictors, observations and agents to improve the performance even more and solve the most complex environments of the challenge.
With the above introductions you will solve tasks like these and even more...
[Imgur](https://i.imgur.com/oOsz7km.gif)
# RLLib Training
# RLLib Training
The `RLLib_training` folder shows an example of how to train agents with algorithm from implemented in the RLLib library available at: <https://github.com/ray-project/ray/tree/master/python/ray/rllib>
The `RLLib_training` folder shows an example of how to train agents with algorithm from implemented in the RLLib library available at: <https://github.com/ray-project/ray/tree/master/python/ray/rllib>
