In this YouTube video by Peter Whidden (https://www.youtube.com/@peterwhidden), he explores the fascinating journey of training an AI to play Pokémon Red using reinforcement learning.
Over five years of simulated game time, the AI evolves from random button-pressing to successfully catching Pokémon, evolving them, and even defeating gym leaders.
The video highlights the relatable aspects of AI learning, drawing parallels to human curiosity, distractions, and learning from experiences.
The AI’s development process is analyzed, along with the strategies used, and the video concludes with technical details on running the program.
Here are the highlights of this journey:
- An AI learns to play Pokémon Red through reinforcement learning over five years of simulated gameplay.
- The AI’s journey reflects human experiences, from curiosity and exploration to dealing with distractions.
- The presenter delves into the technical details of the AI’s development and how to run the program yourself.
- Reinforcement learning allows AI to learn by trial and error, just like humans.
- Curiosity can lead to both discoveries and distractions, a relatable aspect of AI behavior.
- The AI’s journey from random actions to defeating gym leaders demonstrates the power of reinforcement learning.
- You can explore the technical aspects of the AI’s development and run the program yourself for further understanding.