Reinforcement learning

Concept and definition

Reinforcement learning

What is Reinforcement learning?

Reinforcement learning is a machine learning technique in which an agent learns to make decisions in an interactive environment through the feedback it receives from its action. The agent's goal is to maximise a long-term numerical reward, which is given to it for making the correct decisions in the environment.

Reinforcement learning is based on the concept of trial and error, where the agent learns through continuous interaction with the environment, adjusting its actions according to the rewards and penalties it receives. The agent explores different actions in the environment, observes the results and learns to select the actions that maximise long-term reward.

Reinforcement learning is commonly used in robotics, gaming and process automation applications, where an autonomous agent must learn to make real-time decisions to achieve specific goals.

« Back to glossary

Do you want to get in touch?

CDRs contain data that a telecommunications company collects about phone calls, such as time and length of call. This data can be used in analytical applications.
Fill the form
Share:
Industry 4.0 and its main characteristics

Industry 4.0 or the Fourth Industrial Revolution is based on the integration of digital technologies in the production and processing of goods and services.

Read More »
NPLs and recovery of delinquent portfolios

Normally the acronym NPLs (Non Performing Loans) is used in the financial sector and is a reality in Spanish banks as well as in banks [...].

Read More »
Industry 4.0 key technologies

Industry 4.0 is the name given to the fourth industrial revolution, which is characterized by the inclusion of advanced technologies in production processes.

Read More »
How Gamco revolutionized credit risk management for Bankia

In the dynamic financial world, optimizing the return on available assets is essential to the success of any lender. Gam [...]

Read More »
See more entries
© Gamco 2021, All Rights Reserved - Legal notice - Privacy - Cookies