Upload README.md

README.md

@@ -58,4 +58,17 @@ model-index:
       value: 419.7281740188599 +/- 230.5992870123718
       name: Cumulative Reward
       verified: true
----This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>0</code> with difficulty <code>1</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Aerial Wildfire Suppression**<br>Task: <code>0</code><br>Difficulty: <code>1</code><br>Algorithm: <code>PPO</code><br>Episode Length: <code>3000</code><br>Training <code>max_steps</code>: <code>1800000</code><br>Testing <code>max_steps</code>: <code>180000</code><br><br>Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>Download the [Environment](https://github.com/hivex-research/hivex-environments)
+---
+
+This model serves as the baseline for the **Aerial Wildfire Suppression** environment, trained and tested on task <code>0</code> with difficulty <code>1</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>
+
+Environment: **Aerial Wildfire Suppression**<br>
+Task: <code>0</code><br>
+Difficulty: <code>1</code><br>
+Algorithm: <code>PPO</code><br>
+Episode Length: <code>3000</code><br>
+Training <code>max_steps</code>: <code>1800000</code><br>
+Testing <code>max_steps</code>: <code>180000</code><br><br>
+
+Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>
+Download the [Environment](https://github.com/hivex-research/hivex-environments)