Are you a scientist who wants to test a research problem without building costly and complicated real-world rigs? A self-driving car engineer who wants to test their AI logic in a constrained virtual world? A data scientist who needs to solve a thorny real-world problem without touching a production environment? Have you considered AI problem solving using game engines?
No? This workshop will teach you how to solve AI and ML problems using the Unity game engine, and Google’s TensorFlow for Python.
In this workshop, we’ll teach you ML and AI problem solving with game engines. Learn how you could use a game engine to train, explore, and manipulate intelligence agents that learn.
Game engines are a great place to explore ML and AI. They’re wonderful constrained problem spaces, tiny little ecosystems for you to explore a problem in. Here you can learn how to use them even though you’re not a game developer.
In this session, we’ll look at:
Specifically, this session will:
We’ll explore fun, engaging scenarios, including virtual self-driving cars, bipedal human-like walking robots, and disembodied hands that can play tennis.
This workshop is for non-game developers to learn how they can use game technologies to further their understanding of machine learning fundamentals, and solve problems using a combination of open source tools and (sadly often not open source) game engines. Deep reinforcement learning using virtual environments is the beginning of an exciting new wave of AI.
It’s a bit technical, a bit creative.
Dr Paris Buttfield-Addison is co-founder of Secret Lab, a game development studio based in beautiful Hobart, Australia. Secret Lab builds games and game development tools, including the multi-award-winning ABC Play School iPad games, the BAFTA- and IGF-winning Night in the Woods, the Qantas airlines Joey Playbox games, and the open source Yarn Spinner narrative game framework. Previously, Paris was mobile product manager for Meebo (acquired by Google). Paris particularly enjoys game design, statistics, the blockchain, machine learning, and human-centered technology research and writes technical books on mobile and game development (more than 20 so far) for O’Reilly Media. He holds a degree in medieval history and a PhD in computing. Find him online at http://paris.id.au and @parisba
Marina Rose Geldard, more commonly known as Mars, is a technologist from Down Under in Tasmania. Entering the world of technology relatively late as a mature-age student, she has found her place in the world: an industry where she can apply her lifelong love of mathematics and optimization. She compulsively volunteers at industry events, dabbles in research, and serves on the executive committee for her state’s branch of the Australian Computer Society (ACS) as well as the AUC (http://auc.edu.au). She is currently writing ‘Practical Artificial Intelligence with Swift’, for O’Reilly Media, and working on machine learning projects to improve public safety through public CCTV cameras in her home town of Hobart.
Dr Tim Nugent pretends to be a mobile app developer, game designer, tools builder, researcher, and tech author. When he isn’t busy avoiding being found out as a fraud, Tim spends most of his time designing and creating little apps and games he won’t let anyone see. He also spent a disproportionately long time writing this tiny little bio, most of which was taken up trying to stick a witty sci-fi reference in. . .before he simply gave up. Tim is currently writing ‘Practical AI with Swift’ for O’Reilly Media.
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