From d69b303145c41353899a0ce42fde59f9089f1ec2 Mon Sep 17 00:00:00 2001
From: Jeffrey Shih <34355042+unityjeffrey@users.noreply.github.com>
Date: Thu, 6 Sep 2018 10:20:09 -0700
Subject: [PATCH 1/2] minor grammatical fix

---
 docs/Feature-Memory.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/Feature-Memory.md b/docs/Feature-Memory.md
index 79b8eead50..3e4ef5efb9 100644
--- a/docs/Feature-Memory.md
+++ b/docs/Feature-Memory.md
@@ -1,6 +1,6 @@
 # Memory-enhanced agents using Recurrent Neural Networks
 
-## What are memories for
+## What are memories used for?
 
 Have you ever entered a room to get something and immediately forgot what you
 were looking for? Don't let that happen to your agents.  

From 7479a966646865e50e53417b033a9a34ec47503a Mon Sep 17 00:00:00 2001
From: Jeffrey Shih <34355042+unityjeffrey@users.noreply.github.com>
Date: Thu, 6 Sep 2018 10:30:45 -0700
Subject: [PATCH 2/2] fixed definition in table

---
 docs/Training-ML-Agents.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/docs/Training-ML-Agents.md b/docs/Training-ML-Agents.md
index 17e7966fa6..29945545ae 100644
--- a/docs/Training-ML-Agents.md
+++ b/docs/Training-ML-Agents.md
@@ -158,7 +158,7 @@ after the GameObject containing the Brain component that should use these
 settings. (This GameObject will be a child of the Academy in your scene.)
 Sections for the example environments are included in the provided config file.
 
-| **Setting** | **Description** | **Applies To Trainer**|
+| **Setting** | **Description** | **Applies To Trainer\***|
 | :--         | :--             | :--                   |
 | batch_size | The number of experiences in each iteration of gradient descent.| PPO, BC |
 | batches_per_epoch | In imitation learning, the number of batches of training examples to collect before training the model.| BC |
@@ -183,7 +183,8 @@ Sections for the example environments are included in the provided config file.
 | trainer | The type of training to perform: "ppo" or "imitation".| PPO, BC |
 | use_curiosity | Train using an additional intrinsic reward signal generated from Intrinsic Curiosity Module. | PPO |
 | use_recurrent | Train using a recurrent neural network. See [Using Recurrent Neural Networks](Feature-Memory.md).| PPO, BC |
-|| PPO = Proximal Policy Optimization, BC = Behavioral Cloning (Imitation)) ||
+
+\*PPO = Proximal Policy Optimization, BC = Behavioral Cloning (Imitation)
 
 For specific advice on setting hyperparameters based on the type of training you
 are conducting, see: