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The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition

arXiv 1909.07483 ↗First posted 12 Sep 2019cs.LG cs.AIcited by 16

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Abstract (arXiv)

Recent advances in artificial intelligence have been strongly driven by the use of game environments for training and evaluating agents. Games are often accessible and versatile, with well-defined state-transitions and goals allowing for intensive training and experimentation. However, agents trained in a particular environment are usually tested on the same or slightly varied distributions, and solutions do not necessarily imply any understanding. If we want AI systems that can model and understand their environment, we need environments that explicitly test for this. Inspired by the extensive literature on animal cognition, we present an environment that keeps all the positive elements of standard gaming environments, but is explicitly designed for the testing of animal-like artificial cognition.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Sep 2019.

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Citing papers per year: 2021: 6; 2022: 2; 2023: 2; 2024: 3; 2025: 2; 2026: 1.

16 papers.

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  1. 2021The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AIcited by 64
  2. 2025On Benchmarking Human-Like Intelligence in Machinescited by 24
  3. 2021Capturing the objects of vision with neural networkscited by 21
  4. 2022Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worldscited by 17
  5. 2023Inferring Capabilities from Task Performance with Bayesian Triangulationcited by 13
  6. 2024Adaptive Intelligence: leveraging insights from adaptive behavior in animals to build flexible AI systemscited by 5
  7. 2021OPEn: An Open-ended Physics Environment for Learning Without a Taskcited by 4
  8. 2021Extending Environments To Measure Self-Reflection In Reinforcement Learningcited by 3
  9. 2021Sequential memory improves sample and memory efficiency in Episodic Controlcited by 3
  10. 2023The Animal-AI Environment: A Virtual Laboratory For Comparative Cognition and Artificial Intelligence Researchcited by 2
  11. 2021A learning gap between neuroscience and reinforcement learningcited by 1
  12. 2024Discretization of continuous input spaces in the hippocampal autoencodercited by 1
4 more
  1. 2025NiceWebRL: a Python library for human subject experiments with reinforcement learning environmentscited by 1
  2. 2022AIGenC: An AI generalisation model via creativitycited by 0
  3. 2024Disentangled Representations for Causal Cognitioncited by 0
  4. 2026From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environmentscited by 0