From 3e9e315e5305bfd64987bc5bd9c62ab2ffd2dd0a Mon Sep 17 00:00:00 2001
From: Thomas Simonini <simonini.thomas.pro@gmail.com>
Date: Sat, 3 Dec 2022 11:13:19 +0100
Subject: [PATCH] Update units/en/unit2/bellman-equation.mdx

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
---
 units/en/unit2/bellman-equation.mdx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/units/en/unit2/bellman-equation.mdx b/units/en/unit2/bellman-equation.mdx
index f61ec13..be70441 100644
--- a/units/en/unit2/bellman-equation.mdx
+++ b/units/en/unit2/bellman-equation.mdx
@@ -47,7 +47,7 @@ Which is equivalent to  \\(V(S_{t})\\)  = Immediate reward  \\(R_{t+1}\\)  + Dis
 <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit3/bellman6.jpg" alt="Bellman equation"/>
 
 
-For simplification, here we don't discount, so gamma = 1.
+In the interest of simplicity, here we don't discount, so gamma = 1.
 
 - The value of  \\(V(S_{t+1}) \\)  = Immediate reward  \\(R_{t+2}\\)  + Discounted value of the next state ( \\(gamma * V(S_{t+2})\\) ).
 - And so on.