Reinforcement Learning Onramp


 

웹 브라우저를 통한 MATLAB 액세스

 

유익한 비디오 튜토리얼

 

자동 평가 및 피드백 방식의 실습형 예제

 

Lessons available in English


교육과정 목차


1.

Overview of Reinforcement Learning

Familiarize yourself with reinforcement learning concepts and the course.

  • What is reinforcement learning?
  • Course overview
  • Simulating with a pretrained agent

2.

Defining the Environment

Define how an agent interacts with an environment model.

  • Components of a reinforcement learning model
  • Defining an environment interface
  • Rewards and training
  • Including actions in the reward
  • Connecting a Simulink environment to a MATLAB agent

3.

Defining Agents

Create representations of reinforcement learning agents.

  • Critics and Q values
  • Representing critics for continuous problems
  • Creating neural networks
  • Actors and critics
  • Summary of agents

4.

Training Agents

Use simulation episodes to train an agent.

  • Training
  • Improving training

관련 교육과정

Deep Learning Onramp

영상 인식을 위한 딥러닝 기법을 빠르게 학습할 수 있습니다.

Simulink Onramp

Simulink 의 기본 사용법을 빠르게 학습할 수 있습니다.