Using Behavior Objects to Manage Complexity in Virtual Worlds
  The quality of high-level AI of non-player characters (NPCs) in commercial
open-world games (OWGs) has been increasing during the past years. However, due
to constraints specific to the game industry, this increase has been slow and
it has been driven by larger budgets rather than adoption of new complex AI
techniques. Most of the contemporary AI is still expressed as hard-coded
scripts. The complexity and manageability of the script codebase is one of the
key limiting factors for further AI improvements. In this paper we address this
issue. We present behavior objects - a general approach to development of NPC
behaviors for large OWGs. Behavior objects are inspired by object-oriented
programming and extend the concept of smart objects. Our approach promotes
encapsulation of data and code for multiple related behaviors in one place,
hiding internal details and embedding intelligence in the environment. Behavior
objects are a natural abstraction of five different techniques that we have
implemented to manage AI complexity in an upcoming AAA OWG. We report the
details of the implementations in the context of behavior trees and the lessons
learned during development. Our work should serve as inspiration for AI
architecture designers from both the academia and the industry.
