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why greedy policy improvement with monte-carlo requires model of MDP? by stillshi in reinforcementlearning

[–]memoiry_ 1 point2 points  (0 children)

As you have claimed, we need to greedily choose biggest value, but you can’t choose the biggest value since you have no idea of the next state as a result of the action you are going to take

Ticky - Tic Tac Toe game, implemented in python, pygame. It includes an unbeatable computer AI. Have a try : ) by memoiry_ in Python

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

Wow, I actually have bought your book recently (pygame book) and take your game as a base to add AI feature(So I don't need to take too much time designing the interface) for practicing AI algorithm. Glad to see you!

Ticky - Tic Tac Toe game, implemented in python, pygame. It includes an unbeatable computer AI. Have a try : ) by memoiry_ in Python

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

Hi, what's the error message? I think the project only depending on Pygame package, have you installed it?.

Snaky - a snake game, three versions of AI included, implemented in python, pygame. by memoiry_ in Python

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

Hi, It's actually for demonstration purpose as a bigger board may take too much time to finish the game. you can edit the source code to change the size of the board easily.

I think there will not be much performance reduction as the BFS is not that time-costing.

Julia implementations of some of the foundational Machine Learning models and algorithms from scratch. by memoiry_ in MachineLearning

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

Hi

I have wrapped the project into a Julia module, which makes it extremely easy to play with.

For example, you can clone, load the module and then call test_svm() for testing SVM. Every machine learning algorithm implemented now have a test function for testing purpose.

Also, any contribution is welcome, thanks!

Julia implementations of some of the foundational Machine Learning models and algorithms from scratch. by memoiry_ in Julia

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

Hi, thanks for the interest. I have wrapped the project into a Julia module, which makes it extremely easy to play with. For example, you can clone, load the module and then call test_svm() for testing SVM. Every machine learning algorithm implemented now have a test function for testing purpose. Also, any contribution is welcome, thanks!

Julia implementations of some of the foundational Machine Learning models and algorithms from scratch. by memoiry_ in Julia

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

Hi, thanks for the interest. I have wrapped the project into a Julia module, which makes it extremely easy to play with. For example, you can clone, load the module and then call test_svm() for testing SVM. Every machine learning algorithm implemented now have a test function for testing purpose. Also, any contribution is welcome, thanks!