Definition
A state represents all relevant information needed to determine future behavior in systems like Markov Decision Processes (MDPs). In reinforcement learning, the state encapsulates the environment’s condition, allowing the agent to make optimal decisions. It serves as the foundation for policy evaluation and value function approximation.
Summary
The complete configuration of a system or agent at a specific moment in time.
Key Concepts
- Configuration
- Time-step
- Observation
Use Cases
- Reinforcement learning agents
- Hidden Markov Models
- System monitoring