Winning Isn't Everything: Training Human-Like Agents for Playtesting and Game AI

by   Yunqi Zhao, et al.

Recently, there have been several high-profile achievements of agents learning to play games against humans and beat them. We consider an alternative approach that instead addresses game design for a better player experience by training human-like game agents. Specifically, we study the problem of training game agents in service of the development processes of the game developers that design, build, and operate modern games. We highlight some of the ways in which we think intelligent agents can assist game developers to understand their games, and even to build them. Our early results using the proposed agent framework mark a few steps toward addressing the unique challenges that game developers face.


Winning Isn't Everything: Enhancing Game Development with Intelligent Agents

Recently, there have been several high-profile achievements of agents le...

Entombed: An archaeological examination of an Atari 2600 game

The act and experience of programming is, at its heart, a fundamentally ...

On the Development of Intelligent Agents for MOBA Games

Multiplayer Online Battle Arena (MOBA) is one of the most played game ge...

Exploring Gameplay With AI Agents

The process of playtesting a game is subjective, expensive and incomplet...

Mastering Percolation-like Games with Deep Learning

Though robustness of networks to random attacks has been widely studied,...

A Review on Serious Games for Disaster Relief

Human beings have been affected by disasters from the beginning of life,...

A Bayesian Model for Plan Recognition in RTS Games applied to StarCraft

The task of keyhole (unobtrusive) plan recognition is central to adaptiv...

Please sign up or login with your details

Forgot password? Click here to reset