What are some real-life applications of reinforcement learning?

Some real-life applications of reinforcement learning include:

  • Healthcare. Reinforcement learning can be used to create personalized treatment strategies, known as dynamic treatment regimes (DTRs), for patients with long-term illnesses. The input is a set of clinical observations and assessments of a patient. The outputs are the treatment options or drug dosages for every stage of the patient’s journey.
  • Education. Reinforcement learning can be used to create personalized learning experiences for students. This includes tutoring systems that adapt to student needs, identify knowledge gaps, and suggest customized learning trajectories to enhance educational outcomes.
  • Natural language processing (NLP). Text summarization, question answering, machine translation, and predictive text are all NLP applications using reinforcement learning.
  • Robotics. Deep learning and reinforcement learning can be used to train robots that have the ability to grasp various objects , even objects they have never encountered before. This can, for example, be used in the context of an assembly line.