# An Online Agent-Based Search Approach in Automated Computer Game Testing with Model Construction

arXiv: https://arxiv.org/abs/2211.06936 · HTML: https://mlsanity.com/paper/2211.06936/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2022.

## Built on by (most cited first, 1 of 1)

- [Cooperative Multi-agent Approach for Automated Computer Game Testing](https://mlsanity.com/paper/2405.11347/) (2024)

## Abstract (arXiv)

The complexity of computer games is ever increasing. In this setup, guiding an automated test algorithm to find a solution to solve a testing task in a game's huge interaction space is very challenging. Having a model of a system to automatically generate test cases would have a strong impact on the effectiveness and efficiency of the algorithm. However, manually constructing a model turns out to be expensive and time-consuming. In this study, we propose an online agent-based search approach to solve common testing tasks when testing computer games that also constructs a model of the system on-the-fly based on the given task, which is then exploited to solve the task. To demonstrate the efficiency of our approach, a case study is conducted using a game called Lab Recruits.