Design of Emergent and Adaptive Virtual Players in a War RTS Game

TL;DR

This paper presents a method for creating adaptive virtual players in war RTS games by modeling and evolving their behavior in real time, improving their responsiveness to human player skills.

Contribution

It introduces a novel approach for automatic generation and evolution of virtual players based on real-time player modeling in a war RTS game.

Findings

Preliminary results demonstrate effective adaptation to player skills.

The virtual players exhibit more realistic and less predictable behaviors.

The method enhances the gaming experience by making AI opponents more dynamic.

Abstract

Basically, in (one-player) war Real Time Strategy (wRTS) games a human player controls, in real time, an army consisting of a number of soldiers and her aim is to destroy the opponent's assets where the opponent is a virtual (i.e., non-human player controlled) player that usually consists of a pre-programmed decision-making script. These scripts have usually associated some well-known problems (e.g., predictability, non-rationality, repetitive behaviors, and sensation of artificial stupidity among others). This paper describes a method for the automatic generation of virtual players that adapt to the player skills; this is done by building initially a model of the player behavior in real time during the game, and further evolving the virtual player via this model in-between two games. The paper also shows preliminary results obtained on a one player wRTS game constructed specifically for experimentation.