Week 7 Update
This week has been a mix of reflection, correction, and continued learning. After reviewing my progress from last week, I realized that I had made a mistake with the parameters in the decision boundary graph I created. I had accidentally used values of +24 and -24 for the pole angle range, which led to incorrect information. The correct values should have been +0.4 and -0.4 for the pole angle range, and this error caused a major issue.
The mistake was significant because the wrong parameters gave me information that was the opposite of what I would have gotten if the angle had been correct. This led to a misunderstanding of the agent’s behavior and the way it interacted with the environment. Once I realized the error, I immediately corrected the parameters and generated a new graph.
With the corrected graph, I can now better understand the decision boundaries and how the agent makes decisions. It’s been an eye-opening experience, as it really highlights the importance of precision when working with machine learning models. A small mistake can lead to a completely different interpretation of the data and affect the overall learning process.
As I continue to collect data and analyze the decision boundary graph, I’m gaining more insight into the model’s behavior. I’m excited to continue refining the model and gaining a deeper understanding of how it works.
Thanks for reading, and I’ll keep you updated with my progress!
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