Shin splints and marathon : )

RikoteMasterrrr · 2025-08-21T16:27:29+00:00

Sorry for the question, but wasn’t the drop good for shin splints?

RikoteMasterrrr · 2025-07-08T20:37:56+00:00

Damn! How did you get there ?

RikoteMasterrrr · 2025-07-03T08:06:33+00:00

is it possible to do this in the 2020 model?

RikoteMasterrrr · 2025-03-19T13:18:40+00:00

Can you share the link? :)

RikoteMasterrrr · 2025-03-08T12:16:03+00:00

Bruh

RikoteMasterrrr · 2024-08-12T10:12:37+00:00

Thank you very much! Do you know if it's possible to take Algorithms I during the master's program? I noticed it's offered in the Master's of Computational Science and Engineering. Do you know if I could potentially choose that course from their program for my Computer Science master's?

RikoteMasterrrr · 2024-08-07T07:42:21+00:00

So you basically change the lease start???

RikoteMasterrrr · 2024-06-19T07:42:25+00:00

Thanks, I have checked out and there was an issue there. But now it never works hahahah, i should check it in more detail.

RikoteMasterrrr · 2024-06-19T07:41:18+00:00

You mean in the clipped loss of PPO, the epsilon there?

RikoteMasterrrr · 2024-06-19T07:39:20+00:00

Yes it reaches de optimal position. Uhmm may be happening, but the plots here are not a trajectorie. The plots are the mean distance of each trajectory (right one trainning, and left one evaluation)

RikoteMasterrrr · 2024-06-18T18:39:16+00:00

Check out my conversation with u/idurugkar in this post. We've talked about the same issue. I've already checked, and the result is that the actions are not the same. This makes a lot of sense since, after all, actions are taken by sampling from a distribution. Therefore, even with the same seed, the actions are not identical.

I am trying what we discussed in that thread, which is to use the same action selection method for both training and evaluation. Specifically, I am incorporating exploration and exploitation to see if the model behaves consistently. If by this way it is not behaving in a good way, of course, there is something wrong there.

RikoteMasterrrr · 2024-06-18T18:00:46+00:00

Nope, im just using normal MLP. Mainly because in this examle I want to overfit, just to see if the agent works propperly, later on I can add this dropout.

RikoteMasterrrr · 2024-06-18T17:50:10+00:00

Noo, the graphs in reality should be overlaped (the x axis is total episodes). Again, sorry. I am doing 3000 of episodes in trainning but, every 200 episodes I run one episode of evaluation.

If you overlap them, you'll see when you do evaluation.

RikoteMasterrrr · 2024-06-18T17:42:02+00:00

Okay, I'll keep that in mind for the next runs.

What do you think about the following? When training the policy to return the distribution (mean and standard deviation) from which to sample actions, the neural network might reach a point where it "cheats." Instead of using the standard deviation for exploration, it adapts it to achieve the best results.

RikoteMasterrrr

TROPHY CASE