What is reinforcement learning?

Reinforcement learning is an area of machine learning. It is about taking appropriate action to maximize reward in a particular situation. It is employed by various software and machines to find the best possible behavior or path it should take in a specific situation. In reinforcement learning, as there is no training dataset, so there is no answer, but the reinforcement agent decides what to do to perform the given task. Without a training dataset, it is bound to learn from its experience.


What are the types of reinforcement?

There are two types of reinforcement:

  • Positive Reinforcement: When an event occurs due to a particular behavior and increases the behavior’s strength and frequency. In other words, it has a positive effect on behavior.
  • Negative Reinforcement: It is defined as strengthening the behavior because a negative condition is stopped or avoided.


What are the applications of reinforcement learning?

  • Robotics for industrial automation
  • Machine learning and data processing
  • Creation of training systems that provide custom instruction and materials according to the requirements of users
type your search
Get in touch with us.
Our team is here to help you!


For general inquiries:

For Media Relations:

For Investor Relations:

For Careers:

Before you go, can you please answer a question for us?