Robot Architectures for Believable Game Agents

Abstract

Computer game character design and robotics share many of the same goals and computational constraints. Both attempt to create intelligent artifacts that respond realistically to their environments, in real time, using limited computation resources. Unfortunately, none of the current AI architectures is entirely satisfactory for either field. We discuss some of the issues in believability and computational complexity that are common to both fields, and the types of architectures that have been used in the robotics world to cope with these problems. Then we present a new class of architectures, called role passing architectures which combine the ability to perform high level inference with real-time performance.