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Which AI technique enables robots to learn tasks through trial and error?
- Supervised Learning
- Reinforcement Learning
- Unsupervised Learning
- Transfer Learning
Answer: Reinforcement Learning
Reinforcement Learning trains agents to maximize cumulative reward through interactions with an environment. Used in robotics for manipulation, locomotion, and autonomous navigation. Differs from supervised learning (labeled data) and unsupervised learning (pattern discovery). Critical for autonomous systems and AI applications.