Live coding a self-driving car (without a car)
Who is this presentation for?
- Programmers and AI product managers
Whether you’re 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 your AI logic in a constrained virtual world, a data scientist who needs to solve a thorny real-world problem without touching a production environment, AI problem solving using game engines could be for you.
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. Paris Buttfield-Addison, Mars Geldard, and Tim Nugent explore ML and AI problem solving with game engines. Join them to learn how you could use a game engine to train, explore, and manipulate intelligence agents that learn.
Via live coding, Paris, Mars, and Tim look at how video game engines are a perfect environment to constrain a problem and train an agent; how easy it is to get started using the Unity engine and Google’s TensorFlow for Python; how to build up a model, and use it in the engine, to explore a particular idea or problem; proximal policy optimization (PPO) for generic but useful machine learning; and how deep reinforcement learning using virtual environments is the future of ML.
If you’re not a game developer, don’t worry. This session is for you—learn how to use game technologies to further your understanding of machine learning fundamentals and solve problems using a combination of open source tools, such as TensorFlow and PyTorch, and game engines, such as Unit. See how a quadruped can be trained to walk, explore, fetch, or manipulate a virtual world. Train a car to drive. Teach a disembodied hand to play tennis. They do it all live on stage.
It’s a bit technical, a bit creative, and it’s all on the cutting edge.
- A basic understanding of AI principles
What you'll learn
- Understand why game engines such as Unity are a great biosphere for testing complex AI problems in a cost-effective, engaging, and possibly visual way
Paris Buttfield-Addison is a cofounder 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 Yarn Spinner narrative game framework. Previously, Paris was a mobile product manager for Meebo (acquired by Google). Paris particularly enjoys game design, statistics, blockchain, machine learning, and human-centered technology. He researches and writes technical books on mobile and game development (more than 20 so far) for O’Reilly and is writing Practical AI with Swift and Head First Swift. He holds a degree in medieval history and a PhD in computing. You can find him on Twitter as @parisba.
University of Tasmania
Marina (Mars) Rose Geldard is a researcher from Down Under in Tasmania. Entering the world of technology relatively late as a mature-age student, she’s found her place in the world: an industry where she can apply her lifelong love of mathematics and optimization. When she’s not busy being the most annoyingly eager researcher ever, 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). She’s currently writing Practical Artificial Intelligence with Swift for O’Reilly.
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 his tiny little bio, most of which was taken up trying to stick a witty sci-fi reference in…before he simply gave up. He’s writing Practical Artificial Intelligence with Swift for O’Reilly and building a game for a power transmission company about a naughty quoll. (A quoll is an Australian animal.)
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