In this recording of the live session, you'll learn how to create a machine learning experience that has a basic input (one or two dimensional vector observation), an obvious reward, and simple reset state. Throughout the session, learners will be able to:
Define Machine Learning
Discuss how ML differs from and works with Artificial Intelligence
Identify observations for an ML agent to make in a given Scene
Identify ways to reward the ML agent that will reinforce desired behavior
Script the ML Agent to collect observations about conditions in the scene and calculate rewards accordingly
Script the ML Agent to change behavior based on rewards received
 

Materials

MLAgentsLiveSessionAssets.zip

MachineLearning_LiveSession_TrainTheAgent.JPG

Select your Unity version

Last updated: October 20, 2020

2019.4

Language

English

Also included in

CourseML-Agents: Hummingbirds

Submission Gallery

Hummingbird ML Agents - Finished!

Course project finished

Hummingbirds under training

Finished this course

Hummingbirds

Just a screenshot from a working version of the minigame

Find the target

This agent finds the ball when it randomly appears, it could help to make an NPC to find the objective.

Hummingbirds

AI bots flying.

Hummingbird project (ML-Agents Course)

Course project finished

Humming Bird AI

Humming birds are given five degrees of freedom: movement in any x, y, z direction, pitch, and yaw and must drink nectar from flowers. Flowers are initially red but turn purple after nectar is depleted.

Hummingbird driven by AI

a wonderful ML-Agent tutorial

Live Session - Getting Started with Machine Learning in Unity