Exploring Reinforcement Learning
Reinforcement Learning (RL) is a fascinating area of machine learning where agents learn to make decisions by trial and error, guided by rewards and penalties. 🐸✨
Core Concepts of RL
- Agents: The learners/decision makers.
- Environment: Everything the agent interacts with.
- Policy: The strategy that the agent uses to determine the next action based on the current state.
- Reward Signal: Defines the goal of the RL problem.
Applications of RL
Reinforcement Learning is making waves in various fields such as autonomous driving, robotics, and even training froges to leap across algorithms! 🌐🚗🤖