Machine Learning Agents with Unity ML-Agents SDK

Learn to implement machine learning agents in Unity through this comprehensive live session featuring Arthur Juliani and Hunter Henry from Unity's Machine Learning team. Discover how to transform Unity games and simulations into training environments for intelligent agents using the ML-Agents SDK, which supports Deep Reinforcement Learning, Evolutionary Strategies, and other machine learning methods via a Python API. Master the fundamentals of reinforcement and imitation learning while exploring the complete ML-Agents workflow from setup to implementation. Follow along with hands-on demonstrations using the Push Block example to understand agent components, brain systems, and basic scripting techniques. Gain practical experience in training agents and deploying trained models back into Unity environments, making this session ideal for developers and researchers interested in integrating machine learning capabilities into their Unity projects.

Syllabus

Machine Learning Agents - Introduction [1/10] Live 2018/4/4
Machine Learning Agents - Reinforcement and Imitation Learning [2/10] Live 2018/4/4
Machine Learning Agents - Unity ML Agents Workflow [3/10] Live 2018/4/4
Machine Learning Agents - ML Agents Push Block Example [4/10] Live 2018/4/4
Machine Learning Agents - ML Agent Brains [5/10] Live 2018/4/4
Machine Learning Agents - Push Block Agent Components [6/10] Live 2018/4/4
Machine Learning Agents - Push Agent Basic Script [7/10] Live 2018/4/4
Machine Learning Agents - Training Your Agent [8/10] Live 2018/4/4
Machine Learning Agents - Using Your Trained Brain [9/10] Live 2018/4/4
Machine Learning Agents - Conclusion [10/10] Live 2018/4/4