基于感觉运动回路信息分解的量化形态计算
Quantifying Morphological Computation based on an Information Decomposition of the Sensorimotor Loop
摘要：
近年来，代理人如何受到其体现的影响的问题引起了越来越多的关注。一个新的人工智能领域已经出现，它基于这样一种观点：如果不考虑具体化，就不能理解智能。我们相信，一个正式的方法来量化的具体化的代理的行为的影响是有益的人工生命和人工智能领域。代理人的身体和环境对其行为的贡献也被称为形态计算。因此，在这项工作中，我们提出了一个量化的形态计算，这是基于一个信息分解的感觉运动回路共享，独特和协同的信息。在数值模拟的基础上正式表示的感觉运动回路，我们表明，独特的信息的身体和环境是一个很好的测量形态计算。结果进行比较，我们以前派生的量化形态计算。
英文摘要：
The question how an agent is affected by its embodiment has attracted growing attention in recent years. A new field of artificial intelligence has emerged, which is based on the idea that intelligence cannot be understood without taking into account embodiment. We believe that a formal approach to quantifying the embodiment's effect on the agent's behaviour is beneficial to the fields of artificial life and artificial intelligence. The contribution of an agent's body and environment to its behaviour is also known as morphological computation. Therefore, in this work, we propose a quantification of morphological computation, which is based on an information decomposition of the sensorimotor loop into shared, unique and synergistic information. In numerical simulation based on a formal representation of the sensorimotor loop, we show that the unique information of the body and environment is a good measure for morphological computation. The results are compared to our previously derived quantification of morphological computation.
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