From 856f02b8861e839b4139d6e038d15b69b2a6a9d5 Mon Sep 17 00:00:00 2001
From: gmollard <guillaume.mollard2@gmail.com>
Date: Mon, 20 May 2019 11:15:50 +0000
Subject: [PATCH] Update README.md
---
README.md | 23 ++++++++++++++++-------
1 file changed, 16 insertions(+), 7 deletions(-)
diff --git a/README.md b/README.md
index 0edd669..e55c2ba 100644
--- a/README.md
+++ b/README.md
@@ -3,9 +3,10 @@ This repository allows to run Rail Environment multi agent training with the RLL
It should be clone inside the main flatland repository.
## Installation:
-`pip install ray`
-
-`pip install gin-config`
+```sh
+ $pip install ray
+ $pip install gin-config
+```
To start a grid search on some parameters, you can create a folder containing a config.gin file (see example in `grid_search_configs/n_agents_grid_search/config.gin`.
@@ -14,24 +15,32 @@ Then, you can modify the config.gin file path at the end of the `grid_search_tra
The results will be stored inside the folder, and the learning curves can be visualized in
tensorboard:
-```tensorboard --logdir=/path/to/foler_containing_config_gin_file```
+```
+tensorboard --logdir=/path/to/foler_containing_config_gin_file
+```
## Gin config files
In each config.gin files, all the parameters, except `local_dir` of the `run_experiment` functions have to be specified.
For example, to indicate the number of agents that have to be initialized at the beginning of each simulation, the following line should be added:
-```run_experiment.n_agents = 2```
+```
+run_experiment.n_agents = 2
+```
If several number of agents have to be explored during the experiment, one can pass the following value to the `n_agents` parameter:
-```run_experiment.n_agents = {"grid_search": [2,5]}```
+```
+run_experiment.n_agents = {"grid_search": [2,5]}
+```
which is the way to indicate to the tune library to experiment several values for a parameter.
To reference a class or an object within gin, you should first register it from the `train_experiment.py` script adding the following line:
-```gin.external_configurable(TreeObsForRailEnv)```
+```
+gin.external_configurable(TreeObsForRailEnv)
+```
and then a `TreeObsForRailEnv` object can be referenced in the `config.gin` file:
--
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