Modular Object-Oriented Games: A Task Framework for Reinforcement Learning, Psychology, and Neuroscience
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Abstract (arXiv)
In recent years, trends towards studying simulated games have gained momentum in the fields of artificial intelligence, cognitive science, psychology, and neuroscience. The intersections of these fields have also grown recently, as researchers increasing study such games using both artificial agents and human or animal subjects. However, implementing games can be a time-consuming endeavor and may require a researcher to grapple with complex codebases that are not easily customized. Furthermore, interdisciplinary researchers studying some combination of artificial intelligence, human psychology, and animal neurophysiology face additional challenges, because existing platforms are designed for only one of these domains. Here we introduce Modular Object-Oriented Games, a Python task framework that is lightweight, flexible, customizable, and designed for use by machine learning, psychology, and neurophysiology researchers.
Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). Builds on 7 of its 20 references that are in the map. First posted on arXiv 25 Feb 2021.
Builds on
7 of 20 references.
References · 7
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2.
4 papers.
- 2023From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thoughtcited by 119
- 2021Capturing the objects of vision with neural networkscited by 21
- 2023Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenescited by 13
- 2022Modeling Human Eye Movements with Neural Networks in a Maze-Solving Taskcited by 2
- 2023From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought22 Jun 2023
- 2023Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes19 May 2023
- 2022Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task20 Dec 2022
- 2021Capturing the objects of vision with neural networks7 Sep 2021