Comments (2)
mturnshek
commented on May 27, 2024
1
Thanks for the answer, keep up the good work!
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Pravez
commented on May 27, 2024
Hi,
Currently this library implements the "most simple" form of the DQN. It is absolutely possible to use it with your inputs/outputs/layers, but it will be only the Q function with only the classical experience replay. So It will work out okay but without wonderful results, because of the need of better algorithms. Double Learning et Prioritized Experience Replay will be implemented in the future, but it needs some time ;)
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Related Issues (16)
- Roadmap/Todos for Convolutional learning HOT 1
- How to execute actions (output) HOT 7
- basic example HOT 2
- Issue implementing the step() function
- saving the model HOT 4
- confused about using model HOT 1
- How to save and load the model? HOT 1
- Question: Why are Convolutional Networks not Recommended? HOT 1
- npm out of date; dist missing from release; build not working.
- Example/Documentation update [TFJS expected axis NaN for dense1] HOT 4
- expected dense_Dense1_input to have shape [null,12] but got array with shape [1,14] HOT 1
- Train on a dataset? HOT 1
- Error with example Code at step() HOT 2
- Unknown Loss in example Code HOT 1
- Need more informations about lesson HOT 3
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