How do reinforcement learning algorithms improve the autonomous decision-making capabilities of AI-driven robotic systems?

Reinforcement learning (RL) algorithms enhance AI-driven robotic systems by enabling them to learn optimal actions through trial and error. By receiving rewards or penalties based on their actions, robots iteratively improve their decision-making capabilities, leading to more efficient and adaptive behavior in dynamic environments.