Policy
term_id: policy
Category: basic_concepts
Definition
The term ‘policy’ has dual meanings depending on the context. In general management, it is a guiding principle for decision-making. In Reinforcement Learning (RL), a policy is a core component of an agent’s behavior, defining the mapping from states to actions. It can be deterministic (always choosing the same action for a state) or stochastic (choosing actions based on probabilities). The goal in RL is often to optimize the policy to maximize cumulative reward over time.
Summary
A strategy or plan of action designed to guide decisions and achieve rational outcomes, often used in reinforcement learning to map states to actions.
Key Concepts
- Decision Making
- Reinforcement Learning
- State-Action Mapping
- Optimization
Use Cases
- Training autonomous robots via RL
- Creating business rules for automated approvals
- Developing game-playing AI agents