Reinforcement Learning as a Form of Feedback Loop

Reinforcement learning is a classic example of feedback integration in agentic AI. Agents receive rewards or penalties based on actions taken, forming a feedback loop that guides the agent's policy updates towards maximizing cumulative rewards over time.

Reinforcement learning is a classic example of feedback integration in agentic AI. Agents receive rewards or penalties based on actions taken, forming a feedback loop that guides the agent's policy updates towards maximizing cumulative rewards over time.

Empowered by Artificial Intelligence and the women in tech community.
Like this article?

Interested in sharing your knowledge ?

Learn more about how to contribute.

Sponsor this category.