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| Main Author: | |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.01599 |
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| _version_ | 1866918271748407296 |
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| author | Uchiyama, Ryutaro |
| author_facet | Uchiyama, Ryutaro |
| contents | The vertebrate motor system employs dimensionality-reducing strategies to limit the complexity of movement coordination, for efficient motor control. But when environments are dense with hidden action-outcome contingencies, movement complexity can promote behavioral innovation. Humans, perhaps uniquely, may infer the presence of hidden environmental dynamics from social cues, by drawing upon computational mechanisms shared with Theory of Mind. This proposed "Theory of Environment" supports behavioral innovation by expanding the dimensionality of motor exploration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_01599 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | From Theory of Mind to Theory of Environment: Counterfactual Simulation of Latent Environmental Dynamics Uchiyama, Ryutaro Neurons and Cognition Artificial Intelligence The vertebrate motor system employs dimensionality-reducing strategies to limit the complexity of movement coordination, for efficient motor control. But when environments are dense with hidden action-outcome contingencies, movement complexity can promote behavioral innovation. Humans, perhaps uniquely, may infer the presence of hidden environmental dynamics from social cues, by drawing upon computational mechanisms shared with Theory of Mind. This proposed "Theory of Environment" supports behavioral innovation by expanding the dimensionality of motor exploration. |
| title | From Theory of Mind to Theory of Environment: Counterfactual Simulation of Latent Environmental Dynamics |
| topic | Neurons and Cognition Artificial Intelligence |
| url | https://arxiv.org/abs/2601.01599 |