AMaze: a benchmark generator for sighted maze-navigating agents
The need to provide fair comparisons between agents, especially in the field of Reinforcement Learning, has led to a plethora of benchmarks. While these are devoted to tailor-made problems, they offer with very little degrees of freedom for the experimenter. AMaze is instead a benchmark generator capable of producing human-intelligible environments of arbitrarily high complexity. By using visual cues in a maze-navigation task, the library empowers researchers across a large range of fields.<br>
Authors
- Anna V. Kononova (ORCID: https://orcid.org/0000-0002-4138-7024)
- Kevin Godin-Dubois (ORCID: https://orcid.org/0009-0002-6033-3555)
- Karine Miras (ORCID: https://orcid.org/0000-0003-4942-3488)
Institutions
- Leiden University (NL)
- Vrije Universiteit Amsterdam (NL)
Publication Details
- Journal
- The Journal of Open Source Software
- Published
- 2025-11-10
- DOI
- https://doi.org/10.21105/joss.07208
- Primary Topic
- Multimodal Machine Learning Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek