Toribash
Original Post
DeepTR V2
Hello everyone,


After a little while of absence I'm back on the AI of toribash, this time i'm setting up a sequential neural network with a supervised simulation.
This allows the learning of any mods.


The project is under construction. But it works if you modify it for you.

Everybody can participate, as long as you have the knowledge.


By the way nobody will be able to beat this AI.


Project : https://github.com/Stolym/DeepTR_V2
Clan: Tokugawa
Programming: Github
Exciting, hope to see something of this soon. I recently created a deep learning Toribash AI with my good friend Tom, and so far it's been going quite well. We have a different approach to you, so I'm excited to see what yours does.

Once it's done, we should make them fight!

Good luck!
I think it's just a question of supervision.
Basically we have only one network, which is designed to anticipate and attack because it uses the reward of the current environment so win lost.


Let's imagine now that we do this "like a player":


Action "Move to Point (X Y Z)" 1 model
Action "Dodge" 1 model
Action "Jump Attack" 1 model
Action "...."


You see the principles and on top of that we put a new network that will use this action.


It's the same thing as motion matching with a neural network.
Because the 3D model has a skeleton.


Hope, Join me !


Also I forgot to mention a BIG detail actually this AI is not made for a mod that has structures.


the model scales itself on the floor ("normally" " 99% sure x) ").


PS again: For the data, if anyone has a huge replay file of mod lenshu3ng normal rules (> 5.4).


I also just had an idea we could already see a model that adjusts the balance of the body
Last edited by Chips91; 1 Week Ago at 02:40 PM.
Clan: Tokugawa
Programming: Github
New updates !


- More stable environment.
- Generation before learning.
- Save and Load model weights.


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After 3 hours of training I copy a little his opponent dodge but do not attack.


I think that this is due to the quality of the games and the learning process. In any case 63% ("Accuracy") of the moves are good !
Clan: Tokugawa
Programming: Github