IMPACT 2019: Game AI Architecture: The Problem of Human Authored Behavior – Steve Rabin , DigiPen Institute of Technology - Computer Measurement Group

IMPACT 2019: Game AI Architecture: The Problem of Human Authored Behavior – Steve Rabin , DigiPen Institute of Technology

Queueing laws and understanding weird performance test results - Andre B. Bondi, Software Performance and Scalability Consulting LLC
IMPACT 2019: Queueing laws and understanding weird performance test results – Andre B. Bondi, Software Performance and Scalability Consulting LLC
April 29, 2019
Whitepaper – Preparing for the new data-driven business world
May 6, 2019

IMPACT 2019: Game AI Architecture: The Problem of Human Authored Behavior – Steve Rabin , DigiPen Institute of Technology

Game AI Architecture: The Problem of Human Authored Behavior - Steve Rabin , DigiPen Institute of Technology

Over the last 40 years, game AI professionals have crafted many architectures to allow humans to program agent behavior in video games. These game AI architectures can be thought of as domain specific languages with the goal of being powerful, scalable, modular, expressive, concise, easy to debug, and easy to reason about. We’ll take a tour through a handful of architectures in this unique field and see how each manages to excel. While not directly applicable outside of the game industry, hopefully clever aspects resonate with your own problem space and offer inspiration for your current or future challenges.

To view the full video you must have a CMG membership. Sign up today!

Videos sponsored by:

Verified by MonsterInsights