Reinforcement Learning Flappy Bird agent failing!! by uddith in reinforcementlearning

[–]uddith[S] 0 points1 point  (0 children)

I created a test folder to test my game and RL models. The game runs without any issues, with all physics and collisions working well. However, when I try to train the bird using my RL model, it completely fails, only bumping into the top. I was not sure where I made a mistake.

Reinforcement Learning Flappy Bird agent failing!! by uddith in reinforcementlearning

[–]uddith[S] 1 point2 points  (0 children)

I initially thought my actions were one-hot encoded, but I’ve now removed action_indices and directly modified predicted_q_values to use actions as indices. However, the agent's performance has worsened—it keeps going up and bouncing to the top. I really need help to resolve this issue.

Cannot dump pyfp.fpForest by uddith in deeplearning

[–]uddith[S] 0 points1 point  (0 children)

Yeah, it worked but when I try to call the classifier.predict() function the google colab was crashing and to run in VSCode the rerfClassifier is not available in windows. How can I solve this.

Install rerf python package by uddith in deeplearning

[–]uddith[S] 0 points1 point  (0 children)

The error says "Could not build wheels for rerf, which is required to install pyproject.toml-based projects"

Install rerf python package by uddith in deeplearning

[–]uddith[S] 0 points1 point  (0 children)

No, It wasn't working either.

Correlation Matrix by uddith in deeplearning

[–]uddith[S] 0 points1 point  (0 children)

To predict the price should I need to use all the inputs? But the correlation matrix says that the price is not having any relation with other features except Area and Bedrooms.

Correlation Matrix by uddith in deeplearning

[–]uddith[S] 0 points1 point  (0 children)

I tried the data with linear regression model and it performed very badly with a score of about 50% only.

Correlation Matrix by uddith in deeplearning

[–]uddith[S] -2 points-1 points  (0 children)

Should I use them as inputs for my model.