Optimizing Bitcoin trading bot model and reward strategy to increase profitability #4

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Добавлено 3 года назад от ВадикБасюк

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Let’s improve our deep RL Bitcoin trading agent code to make even more money with a better reward strategy and by testing different model structures

In the last tutorial, we used deep reinforcement learning to create a Bitcoin trading agent that could beat the market. Although our agent was profitable compared to random actions, the results weren’t all that impressive, so this time we’re going to step it up and we’ll try to implement few more improvements with the reward system and we’ll test how our profitability depends on Neural Network model structure. Although, we’ll test everything with our code and of course, you’ll be able to download everything from my Github repository.

Text version tutorial: RL-BTC-BOT-reward/
GitHub code: pythonlessons/RL-Bitcoin-trading-bot/tree/main/RL-Bitcoin-trading-bot_4

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