diff --git a/README.md b/README.md
index 4da1a0687c44c8a29412ad6e90489db068b4bb21..339f740764b28f4f540312175a30c9a672d8267a 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,8 @@ A python implementation of symbolic policy for interpretable reinforcement learn
 ### Installing dependencies
 - clone this repo
 - install with ` python -m pip install -r requirement.txt ` for base installation (no pygraphiz)
-- install with ` python -m pip install -r requirement_with_pygrphivz.txt `  if you want to visualize program easily   
+- install with ` python -m pip install -r requirement_with_pygrphivz.txt `  if you want to visualize program easily
+- install with `conda env create -f environment.yml` if you want to create a separate python environment with all the dependencies
 
 ## How to use
 ### Core functions
@@ -73,3 +74,18 @@ seed: #set seed for random
 
 ## See the result
 Once an experiment is finished, you can see inspect results like in `tutorial.ipynb`. This notebook show how to see and run an individual from a saved population.
+
+## Environments
+
+| **Environment**       | **Name**                            |
+|-----------------------|-------------------------------------|
+| Cartpole              | CartPole-v1                         |
+| Acrobot               | Acrobot-v1                          |
+| MountainCar           | MountainCarContinuous-v0            |
+| Pendulum              | Pendulum-v0                         |
+| InvDoublePend         | InvertedDoublePendulumBulletEnv-v0  |
+| InvPendSwingUp        | InvertedPendulumSwingupBulletEnv-v0 |
+| LunarLander           | LunarLanderContinuous-v2            |
+| BipedalWalker         | BipedalWalker-v3                    |
+| BipedalWalkerHardCore |                                     |
+| Hopper                | HopperBulletEnv-v0                  |