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ALE Transfer Learning

Final Presentation

- Abhay Atrish

- Kunal Kotwani

- Kushal D'Souza

- Prabhjot Singh

Overview

Introduction

Goals:

- Train an autonomous agent to learn how to play an arcade-based game

- Identify benefits of applying transfer learning to games within the Arcade Learning Environment(ALE) belonging to a similar genre.

Introduction

Highlights:

- Utilization of open source libraries Open AI Gym and PPO to implement reinforcement learning

- Conversion of game states to a latent space representation for Mario and Contra

Trailer

Results

Results

- Faster Learning w.r.t Vanilla

- 10% improvement over Vanilla

Conclusion

Conclusion

- Successfully trained an agent for Mario and Contra using PPO algorithm.

- Successfully verified the application of transfer learning approach for games within the same genre.

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