Beginner · Reinforcement Learning
Feedback
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. Feedback is the evaluation of an agent's action, providing information about its success or failure to guide future behavior.
Technical Definition
Feedback is the evaluation of an agent's action, providing information about its success or failure to guide future behavior.
How it works
In the context of agents and reinforcement learning, feedback is the signal received after an action is taken. This feedback typically indicates whether the action was beneficial (reward) or detrimental (penalty) in achieving a goal. It's crucial for the agent to learn and adapt its strategy over time.
Related Concepts
- Reinforcement Learning — A paradigm where an agent learns to make decisions by receiving rewards or penalties from its environment through trial and error.
- AI Agent — An AI system that autonomously plans, uses tools, and takes actions to accomplish goals through iterative reasoning.