What is Reinforcement Learning Agent?
It is a software unit that learns to make the right decisions by gaining rewards through trial and error.
Overview
This artificial intelligence unit receives a reward for every correct move it makes while moving in an environment and a penalty for a wrong move. Over time, he discovers the best strategy to reap the most rewards. It has a self-developing learning process.
How it works
The system first makes random moves, analyzes the results, and saves the successful results in its memory to make more accurate decisions next time.
Where it is used
It is widely used in robotic systems, gaming artificial intelligence, and automated stock trading strategies.
Commonly confused with
Unlike bots that work with standard programmed rules, it creates its own strategy with experience.
Frequently asked questions
Do these units always get it right?
No, they just try to find the most efficient path according to the given reward mechanism.
Related terms
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This explanation was written in plain language for TreScout · translated from the Turkish original. If something looks wrong or missing, write to hello@trescout.com. Read in Turkish →