diff --git a/units/en/_toctree.yml b/units/en/_toctree.yml
index 2c08589..85835d9 100644
--- a/units/en/_toctree.yml
+++ b/units/en/_toctree.yml
@@ -213,6 +213,8 @@
   - local: unitbonus3/offline-online
     title: Offline vs. Online Reinforcement Learning
   - local: unitbonus3/rlhf
+    title: Generalisation in Reinforcement Learning
+  - local: unitbonus3/generalisation
     title: Reinforcement Learning from Human Feedback
   - local: unitbonus3/decision-transformers
     title: Decision Transformers and Offline RL
diff --git a/units/en/unitbonus3/generalisation.mdx b/units/en/unitbonus3/generalisation.mdx
new file mode 100644
index 0000000..27f38c7
--- /dev/null
+++ b/units/en/unitbonus3/generalisation.mdx
@@ -0,0 +1,12 @@
+# Generalization in Reinforcement Learning
+
+Generalization plays a pivotal role in the realm of Reinforcement Learning. While **RL algorithms demonstrate good performance in controlled environments**, the real world presents a **unique challenge due to its non-stationary and open-ended nature**.
+
+As a result, the development of RL algorithms that stay robust in the face of environmental variations, coupled with the capability to transfer and adapt to uncharted yet analogous tasks and settings, becomes fundamental for real world application of RL.
+
+If you're interested to dive deeper into this research subject, we recommend exploring the following resource:
+
+- [Generalization in Reinforcement Learning by Robert Kirk](https://robertkirk.github.io/2022/01/17/generalisation-in-reinforcement-learning-survey.html): this comprehensive survey provides an insightful **overview of the concept of generalization in RL**, making it an excellent starting point for your exploration.
+
+- [Improving Generalization in Reinforcement Learning using Policy Similarity Embeddings](https://blog.research.google/2021/09/improving-generalization-in.html?m=1)
+
diff --git a/units/en/unitbonus3/learning-agents.mdx b/units/en/unitbonus3/learning-agents.mdx
index 51f92a3..e775499 100644
--- a/units/en/unitbonus3/learning-agents.mdx
+++ b/units/en/unitbonus3/learning-agents.mdx
@@ -24,6 +24,8 @@ Armed with the basics, **you're now prepared to play with Learning Agents**:
 
 4. [Teach a Car to Drive using Reinforcement Learning in Learning Agents](https://dev.epicgames.com/community/learning/tutorials/qj2O/unreal-engine-learning-to-drive).
 
+5. [Check Imitation Learning with the Unreal Engine 5.3 Learning Agents Plugin](https://www.youtube.com/watch?v=NwYUNlFvajQ)
+
 ## Case 2: I'm familiar with Unreal
 
 For those already acquainted with Unreal Engine, you can jump straight into Learning Agents with these two tutorials:
@@ -31,3 +33,5 @@ For those already acquainted with Unreal Engine, you can jump straight into Lear
 1. Get the Big Picture of Learning Agents by [reading this informative overview](https://dev.epicgames.com/community/learning/tutorials/8OWY/unreal-engine-learning-agents-introduction).
 
 2. [Teach a Car to Drive using Reinforcement Learning in Learning Agents](https://dev.epicgames.com/community/learning/tutorials/qj2O/unreal-engine-learning-to-drive). .
+
+3. [Check Imitation Learning with the Unreal Engine 5.3 Learning Agents Plugin](https://www.youtube.com/watch?v=NwYUNlFvajQ)
\ No newline at end of file