#AIImpactOnForex Reinforcement Learning in Currency Trading Models Reinforcement learning (RL) is an AI approach where models learn to make trading decisions by interacting with the currency market environment and optimizing their strategies through trial and error. In currency trading, RL agents are trained to maximize cumulative returns by deciding when to buy, sell, or hold currencies based on market data. Techniques like Q-learning, Deep Q-Networks (DQN), and Proximal Policy Optimization (PPO) are commonly used. RL models can adapt to changing market dynamics without relying on pre-defined rules, making them highly flexible. However, they require careful training to handle market volatility and avoid overfitting to historical data.