From 6fb1e33d699d086fd2584ade7b6e1880fcf87d83 Mon Sep 17 00:00:00 2001
From: mlerik <baerenjesus@gmail.com>
Date: Mon, 15 Jul 2019 14:38:38 +0000
Subject: [PATCH] Update Multi_Agent_Training_Intro.md

---
 torch_training/Multi_Agent_Training_Intro.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/torch_training/Multi_Agent_Training_Intro.md b/torch_training/Multi_Agent_Training_Intro.md
index b69467e..6eb0842 100644
--- a/torch_training/Multi_Agent_Training_Intro.md
+++ b/torch_training/Multi_Agent_Training_Intro.md
@@ -1,6 +1,6 @@
-# How to train an Agent on Flatland
+# How to train multiple Agents on Flatland
 Quick introduction on how to train a simple DQN agent using Flatland and Pytorch. At the end of this Tutorial you should be able to train a single agent to navigate in Flatland.
-We use the `training_navigation.py` ([here](https://gitlab.aicrowd.com/flatland/baselines/blob/master/torch_training/training_navigation.py)) file to train a simple agent with the tree observation to solve the navigation task.
+We use the `multi_agent_training.py` ([here](https://gitlab.aicrowd.com/flatland/baselines/blob/master/torch_training/multi_agent_training.py)) file to train multiple agents on the avoid conflicts task.
 
 ## Actions in Flatland
 Flatland is a railway simulation. Thus the actions of an agent are strongly limited to the railway network. This means that in many cases not all actions are valid.
-- 
GitLab