In the realm of
cryptocurrency trading, the application of reinforcement learning holds immense potential. Could you elaborate on how this machine learning technique could be leveraged to optimize trading strategies? I'm particularly interested in understanding how an agent could learn from past market data, adjust its trading behavior based on rewards and penalties, and ultimately arrive at strategies that maximize profits while minimizing risks. Additionally, I'd like to know about the challenges that arise in implementing reinforcement learning for crypto trading and how they might be addressed.