Can deep reinforcement learning improve backtest overfitting for cryptocurrency trading?

Could you elaborate on the potential of deep reinforcement learning to mitigate backtest overfitting in cryptocurrency trading? Many practitioners struggle with optimizing strategies in the rapidly fluctuating cryptocurrency markets. Is deep reinforcement learning a viable solution to this challenge? How does it compare to traditional backtesting methods? What are the key factors to consider in implementing deep reinforcement learning for cryptocurrency trading, and how might it improve the robustness and generalizability of trading strategies?