Description

Reinforcement Learning and OpenAI Gym

Reinforcement Learning and OpenAI Gym
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 44M | 254 MB Genre: eLearning | Language: English

This course provides an introduction to the field of reinforcement learning and the use of OpenAI Gym software.

How this course will help you

It details the terminology and core

concepts of illustrates how OpenAI Gym software incorporates those core concepts,

and shows you how to code solutions for  problems present in

simple mazes and complex Atari games. Requirements include basic

Python programming experience, basic math knowledge, familiarity with the

Linux and Bash terminal, and an understanding of how to use Jupyter notebooks.

Master the basic terminology, concepts, and uses of reinforcement learning

Understand how to install and manage reinforcement learning software

How this course will help you

Learn about OpenAI Gym’s API and how to use it to test reinforcement learning algorithms

Discover how to determine

if a problem is best solved with reinforcement learning

Explore the code used to solve reinforcement learning problems in computer games

Reinforcement learning is a type of machine learning that rewards an agent for taking actions

that are deemed to

 

OpenAI Gym is a toolkit that allows agents

to be trained and tested

on many different environments.

How this course will help you

OpenAI Gym currently includes many different environments,

such as a CartPole-v0 environment where

 

an arm wrestling environment where two agents must

push each other away from the center of the table and a

Q-learning environment where an agent must learn how to get food  agents.