MiS Preprint Repository

We have decided to discontinue the publication of preprints on our preprint server as of 1 March 2024. The publication culture within mathematics has changed so much due to the rise of repositories such as ArXiV ( that we are encouraging all institute members to make their preprints available there. An institute's repository in its previous form is, therefore, unnecessary. The preprints published to date will remain available here, but we will not add any new preprints here.

MiS Preprint

Quantifying Morphological Computation

Keyan Zahedi and Nihat Ay


The field of embodied intelligence emphasises the importance of the morphology and environment with respect to the behaviour of a cognitive system. The contribution of the morphology to the behaviour, commonly known as \emph{morphological computation}, is well-recognised in this community. We believe that the field would benefit from a formalisation of this concept as we would like to ask how much the morphology and the environment contribute to an embodied agent's behaviour, or how an embodied agent can maximise the exploitation of its morphology within its environment. In this work we derive two concepts of measuring morphological computation, and we discuss their relation to the Information Bottleneck Method. The first concepts asks how much the world contributes to the overall behaviour and the second concept asks how much the agent's action contributes to a behaviour. Various measures are derived from the concepts and validated in two experiments which highlight their strengths and weaknesses.

MSC Codes:
68T01, 94A17
07.05.Mh, 89.70.-a
Embodied Artificial Intelligence, Morphological Computation, information theory, Sensori-Motor Loop

Related publications

2013 Journal Open Access
Keyan Ghazi-Zahedi and Nihat Ay

Quantifying morphological computation

In: Entropy, 15 (2013) 5, pp. 1887-1915