Reinforcement Learning
Agent learning, control tasks, and environment interactions
Reinforcement learning tasks involve agents that learn through trial and error.
The agent:
- takes actions
- receives rewards or penalties
- learns to maximize rewards over time
Common RL Tasks
- Reinforcement Learning: Train agents via rewards and interactions
- Robotics: Control and decision-making for robotic systems
Dimensionality Reduction
Reducing the number of features while preserving essential information
AI Model Families
Groups of related ML models. This is the overview on concrete implementations of AI. These implementations are commonly called "Model" and different kinds of model architectures generally aim at solving different problems.