Introduction to Reinforcement Learning
Reinforcement Learning (RL) is an exciting area of machine learning where agents learn to make decisions by interacting with an environment. It's like teaching a Froge how to jump to the best lily pads, balancing exploration and exploitation. 🐸
Core Concepts
- Agent: The learner or decision maker.
- Environment: The setting the agent interacts with.
- Actions: Choices the agent can make.
- Rewards: Feedback from the environment, a signal of success or failure.
- Policy: Strategy that the agent employs to determine the next action based on the current state.
Applications
From robotics to gaming, and even to financial trading, reinforcement learning is widely applied.
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