Exploring Gameplay With AI Agents

The process of playtesting a game is subjective, expensive and incomplete. In this paper, we present a playtesting approach that explores the game space with automated agents and collects data to answer questions posed by the designers. Rather than have agents interacting with an actual game client, this approach recreates the bare bone mechanics of the game as a separate system. Our agent is able to play in minutes what would take testers days of organic gameplay. The analysis of thousands of game simulations exposed imbalances in game actions, identified inconsequential rewards and evaluated the effectiveness of optional strategic choices. Our test case game, The Sims Mobile, was recently released and the findings shown here influenced design changes that resulted in improved player experience.

READ FULL TEXT

page 5

page 6

research
07/18/2018

Generating Levels That Teach Mechanics

The automatic generation of game tutorials is a challenging AI problem. ...
research
03/25/2019

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

Recently, there have been several high-profile achievements of agents le...
research
06/22/2018

Game AI Research with Fast Planet Wars Variants

This paper describes a new implementation of Planet Wars, designed from ...
research
06/15/2021

Rinascimento: searching the behaviour space of Splendor

The use of Artificial Intelligence (AI) for play-testing is still on the...
research
08/13/2019

Playing log(N)-Questions over Sentences

We propose a two-agent game wherein a questioner must be able to conjure...
research
07/26/2021

Playtesting: What is Beyond Personas

Playtesting is an essential step in the game design process. Game design...
research
02/19/2019

Agent Madoff: A Heuristic-Based Negotiation Agent For The Diplomacy Strategy Game

In this paper, we present the strategy of Agent Madoff, which is a heuri...

Please sign up or login with your details

Forgot password? Click here to reset