A Framework for Complementary Companion Character Behavior in Video Games

TL;DR

This paper introduces a framework for controlling companion characters in video games to perform complementary actions that support player strategies, using dynamic region targeting and adaptive behavior.

Contribution

It presents a novel framework that enables AI companions to adaptively perform supportive actions based on player behavior and game state, enhancing gameplay experience.

Findings

Participants reacted positively to the companion behavior

Majority would consider using the framework in future games

Framework effectively supports complementary companion actions

Abstract

We propose a game development framework capable of governing the behavior of complementary companions in a video game. A "complementary" action is contrasted with a mimicking action and is defined as any action by a friendly non-player character that furthers the player's strategy. This is determined through a combination of both player action and game state prediction processes while allowing the AI companion to experiment. We determine the location of interest for companion actions based on a dynamic set of regions customized to the individual player. A user study shows promising results; a majority of participants familiar with game design react positively to the companion behavior, stating that they would consider using the frame-work in future games themselves.