updated submission information

Author: avaamini

lab3/solutions/RL_Solution.ipynb

@@ -911,7 +911,7 @@
         "id": "TIlwIgBP3Js6"
       },
       "source": [
-        "## 3.10 Conclusion\n",
+        "## 3.10 Conclusion and submission information\n",
         "\n",
         "That's it! Congratulations on training two RL agents and putting them to the test! We encourage you to consider the following:\n",
         "\n",
@@ -921,7 +921,14 @@
         "* How does the complexity of Pong relative to Cartpole alter the rate at which the agent learns and its performance? \n",
         "* What are some things you could change about the agent or the learning process to potentially improve performance?\n",
         "\n",
-        "If you want to go further, try to optimize your model to achieve the best performance! **[Email us](mailto:[email protected]) a copy of your notebook with the Pong training executed AND a saved video of your Pong agent competing! We'll give out prizes to the best performers!**"
+        "Try to optimize your model to achieve improved performance.  **MIT students and affiliates will be eligible for prizes during the IAP offering.** To enter the competition, please [email us](mailto:[email protected]) with your name and the following:\n",
+        "\n",
+        "* Jupyter notebook with the code you used to generate your results, **with the Pong training executed**;\n",
+        "* saved video of your Pong agent competing;\n",
+        "* a description and/or diagram of the architecture, settings, and hyperparameters you used to generate your result -- if there are any additional or interesting modifications you made to the template code, please include these in your description;\n",
+        "* discussion of why these modifications helped improve performance.\n",
+        "\n",
+        "Good luck!"
       ]
     }
   ]