Action-based Character AI in Video-games with CogBots Architecture: A Preliminary Report
This work addresses NPC behavior design for video game developers, but it appears incremental as it adapts existing autonomous agent concepts to gaming.
The authors proposed the CogBots architecture for non-player character (NPC) interaction in video games, abstracting tasks into perception, deliberation, control, and action components, and demonstrated its application to NPC navigation under incomplete information about obstacles.
In this paper we propose an architecture for specifying the interaction of non-player characters (NPCs) in the game-world in a way that abstracts common tasks in four main conceptual components, namely perception, deliberation, control, action. We argue that this architecture, inspired by AI research on autonomous agents and robots, can offer a number of benefits in the form of abstraction, modularity, re-usability and higher degrees of personalization for the behavior of each NPC. We also show how this architecture can be used to tackle a simple scenario related to the navigation of NPCs under incomplete information about the obstacles that may obstruct the various way-points in the game, in a simple and effective way.