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5 devlogs
13h 46m 23s

A working trained through reinforcment learning model for texas holdem

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liquidcat

I trained models though evolution training, all is left is to just make it useable with good inteface

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liquidcat

yeah, so the issue is that LSTM’s are not fit to train through evolutionary technics, I remade encoder to return winrate and confidence of other players and implmeneted simple MLP which can be trained with this technic

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liquidcat

I cahnged architecture of my model to have 2 heads, I also worked on fully working model, right now it just needs improvments in encoder part.

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liquidcat

I changed env for one suited for table with more than 2 players, right now I am designin model and encoder for data, simulating poker is done and system of reward is done, only part left in training loop is to add DL parts to it.

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liquidcat

All folder architecture + envs is done

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