What is Reinforcement Learning?
Reinforcement Learning (RL) is an area of machine learning inspired by behavioral psychology. It is concerned with how software agents ought to take actions in an environment to maximize some notion of cumulative reward. 🌟
In simple terms, it's like teaching a froge to jump on a lilypad without falling into the water by giving it rewards when it succeeds!
Key Concepts
- Agent: The learner or decision maker (our froge!).
- Environment: Where the agent learns and decides what actions to take.
- Rewards: Feedback received by the agent after taking actions.
- Policy: The strategy the agent employs to determine next action based on the current state.
Get Involved
Want to test your skills? Try our latest workshop on building a mini RL agent that learns to play a simple game! 🎮