- Step1: Clone the repository from GitHub.
- Step2: Install Python dependencies via pip.
- Step3: Download and prepare historical market data.
- Step4: Configure environment settings and reward functions.
- Step5: Train the reinforcement learning agent on the data.
- Step6: Run backtests to evaluate strategy performance.
- Step7: Connect to a broker API for live simulation or deployment.