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The quality of high-level AI of nonplayer 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 <italic> behavior objects</italic> (BO)&#x2014;a general approach to development of NPC behaviors for large OWGs. BOs 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. BOs 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 study should serve as an inspiration for AI architecture designers from both the academia and the industry.

Using Behavior Objects to Manage Complexity in Virtual Worlds