MIMo: A Multi-Modal Infant Model for Studying Cognitive Development

Dominik Mattern, Pierre Schumacher, Francisco M. López, Marcel C. Raabe, Markus R. Ernst +2 more
12/7/2023
cs.AIcs.LG

Official code: trieschlab/MIMo (50 stars, MIT, last commit 2026-04-04).

Abstract

Human intelligence and human consciousness emerge gradually during the process of cognitive development. Understanding this development is an essential aspect of understanding the human mind and may facilitate the construction of artificial minds with similar properties. Importantly, human cognitive development relies on embodied interactions with the physical and social environment, which is perceived via complementary sensory modalities. These interactions allow the developing mind to probe the causal structure of the world. This is in stark contrast to common machine learning approaches, e.g., for large language models, which are merely passively ``digesting'' large amounts of training data, but are not in control of their sensory inputs. However, computational modeling of the kind of self-determined embodied interactions that lead to human intelligence and consciousness is a formidable challenge. Here we present MIMo, an open-source multi-modal infant model for studying early cognitive development through computer simulations. MIMo's body is modeled after an 18-month-old child with detailed five-fingered hands. MIMo perceives its surroundings via binocular vision, a vestibular system, proprioception, and touch perception through a full-body virtual skin, while two different actuation models allow control of his body. We describe the design and interfaces of MIMo and provide examples illustrating its use. All code is available at https://github.com/trieschlab/MIMo .

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trieschlab/MIMoOfficial100%
MIT
5014PythonJan 30, 20226 months agoMIT

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@article{mattern2023mimo,
  title  = {MIMo: A Multi-Modal Infant Model for Studying Cognitive Development},
  author = {Dominik Mattern and Pierre Schumacher and Francisco M. López and Marcel C. Raabe and Markus R. Ernst and Arthur Aubret and Jochen Triesch},
  year   = {2023},
  eprint = {2312.04318},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2312.04318v1}
}

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