Definition
Reinforcement is a fundamental psychological and computational mechanism where an agent’s actions are shaped by consequences. In machine learning, it involves providing positive feedback (rewards) for desirable outcomes and negative feedback (penalties) for undesirable ones. This feedback loop allows systems to learn optimal strategies over time without explicit supervision, focusing on maximizing cumulative long-term reward rather than immediate accuracy.
Summary
Reinforcement refers to the process of modifying behavior through rewards or punishments to optimize decision-making.
Key Concepts
- Reward Signal
- Feedback Loop
- Behavior Shaping
- Optimization
Use Cases
- Robotics control
- Game playing agents
- Resource management