Reinforcement Learning
/ˌriːɪnˈfɔːrsmənt ˈlɜːrnɪŋ/
A machine learning paradigm where agents learn by interacting with an environment and receiving rewards or penalties.
In italiano: Reinforcement LearningRL agents learn optimal policies through trial and error. Key concepts include states, actions, rewards, and Q-learning. Used in game playing (AlphaGo), robotics, and autonomous systems.
Examples
- AlphaGo defeating world champions
- Robotic control systems
- Autonomous driving decisions