Previous Page

Reinforcement Learning: Essentials

Reinforcement Learning: Essentials


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Explore reinforcement learning and its components, which can be used to help develop critical algorithms for decision making.



Expected Duration (hours)
0.5

Lesson Objectives

Reinforcement Learning: Essentials

  • define reinforcement learning and describe its essential elements
  • recognize the key differences between the reinforcement learning and machine learning paradigms
  • depict the flow of reinforcement learning using agent, action, and environment
  • describe different state change scenarios and transition processes in reinforcement learning
  • recognize the role of rewards in reinforcement learning
  • list the essential steps agents take to make decisions in reinforcement learning
  • recognize prominent reinforcement learning environment types
  • install OpenAI Gym and OpenAI Universe
  • list reinforcement learning elements, agents involved in the process and the steps they take, and reinforcement learning environments
  • Course Number:
    it_mlrlfndj_01_enus

    Expertise Level
    Intermediate