Keen to experiment with coordinated search? The source code for the coordinated search tutorial is now available, along with bonus access to The AI Sandbox. You'll find a simple tactical pathfinder as well as a corridor map implementation, written in Python with extensive comments.
In this introductory tutorial about computer vision, you'll learn about homographic transformations, why they are useful and how they work. After that, you'll see how they can be applied to detecting the position of a camera in space, or the relative position of a projector. Then you'll also hear about useful computer vision algorithms, and why performance is often critical for such augmented reality ...
Crowd and ambient life simulation are having a huge impact on the visual effects industry. Many tools and and techniques are required to animate convincing crowds in films (Drakula Untold), TV series (The Walking Dead) and adverts. This interview digs into the technology using examples, and how these ideas and tools can be applied within real-time simulations and games.
Both commonly used techniques for simulating movement in groups have their challenges. Steering does not look particularly human-like, and velocity-based approaches like ORCA don't scale very well to larger crowds and have their own challenges.
This recording digs into most important ideas and techniques in Game AI from GDC last month, including the AI Summit, as well as big trends take-aways from the conference. You'll hear about the AI, animation and procedural generation in games such as Sunset Overdrive, Watch_Dogs, Galak-Z, and more.
Using Python is one of the simplest ways to get started with deep learning and neural networks. This tutorial will show you how you can get up and running with PyLearn2 via a simple wrapper library, and the various issues and questions you need to be considering in practice to get things working efficiently and reliably.
Keen to experiment with tactical pathfinding? The source code for the flanking tutorial is now available, along with bonus access to The AI Sandbox. You'll find a grid-based tactical pathfinder as well as one based on a corridor map, written in Python with extensive comments.
Over the past few years, deep learning has revolutionized the technology sector by providing significantly better results on classification or prediction problems that were previously impractical for machine learning. What are the benefit for game developers? What's the catch? This presentation is a practical introduction to deep neural networks, using millions of public player profiles and thousands of games ...
This tutorial with Spyridon Samothrakis will cover the techniques and tricks for applying Reinforcement Learning using Neural Networks, particularly to the problem of PlanetWars. You'll learn the different approaches for solving the problem, what needs to be done for it to work at all, and how best to tear your hair out when it doesn't work!
This tutorial will show you how to write bots for The Resistance that are both intelligent and chatty! In particular, you'll learn about building bots that are able to run searches to determine the best course of action, as well as how to use text-to-speech (TTS) and speech-to-text facilities in the framework. If you're curious about building AI for board/card games, find out more in this broadcast!