SNHU AlphaGo and AlphaGo Zero Discussion

This week you have spent some time exploring advanced concepts in reinforcement learning. In this discussion, you will be asked to explore the programs AlphaGo and AlphaGo Zero. You will need to use resources to support your points, and may use readings from the module resources as well as your own research. Below are a few potential resources from the Shapiro Library to get you started, but you are encouraged to find additional sources.

NOTE: You are not required to read all of these articles. Review the abstracts to select the articles that apply best to the prompts you want to discuss.

• AlphaGo Zero: Starting From Scratch
• Mastering the Game of Go Without Human Knowledge
• Demystifying AlphaGo Zero as AlphaGo GAN
• Deep New: The Shifting Narratives of Artificial Intelligence From Deep Blue and AlphaGo
• Where Does AlphaGo Go
• Mastering Chess and Shogi by Self-Play With a General Reinforcement Learning Algorithm
• AlphaGo, Deep Learning, and the Future of the Human Microscopist

For your initial post, choose two of the following prompts and write a response of 2àparagraphs total. Your answer must include references to resources used, properly cited in APA format.

• What are the differences between AlphaGo Zero and its predecessors? How did these differences improve AlphaGo Zero’s performance?
• How do the neural networks and reinforcement learning algorithms interact in AlphaGo Zero? How does this affect performance?
• How does the thinking of programs such as AlphaGo and AlphaGo Zero compare with how humans think? How does this affect gameplay? How does this affect our perception of AI?
• What implications does AlphaGo or AlphaGo Zero’s performance have for future AI developments?