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.

翻译：脊椎动物运动系统采用降维策略来限制运动协调的复杂性，以实现高效的运动控制。然而，当环境中充满隐藏的动作-结果关联时，运动复杂性可以促进行为创新。人类或许独特地能够通过利用与心智理论共享的计算机制，从社会线索中推断隐藏环境动态的存在。这一提出的“环境理论”通过扩展运动探索的维度来支持行为创新。