The purpose of this paper is to argue against the claim that morphological computation is substantially different from other kinds of physical computation. I show that some (but not all) purported cases of morphological computation do not count as specifically computational, and that those that do are solely physical computational systems. These latter cases are not, however, specific enough: all computational systems, not only morphological ones, may (and sometimes should) be studied in various ways, including their energy efficiency, cost, reliability, (...) and durability. Second, I critically analyze the notion of “offloading” computation to the morphology of an agent or robot, by showing that, literally, computation is sometimes not offloaded but simply avoided. Third, I point out that while the morphology of any agent is indicative of the environment that it is adapted to, or informative about that environment, it does not follow that every agent has access to its morphology as the model of its environment. (shrink)

In this paper, the Author reviewed the typical objections against the claim that brains are computers, or, to be more precise, information-processing mechanisms. By showing that practically all the popular objections are based on uncharitable interpretations of the claim, he argues that the claim is likely to be true, relevant to contemporary cognitive science, and non-trivial.

The body is a highly complex, coordinated system engaged in coping with many environmental problems. It can be considered as some sort of opportunity or obstacle, with which internal processing must deal. Internal processing must take into account the possibilities and limitations of the particular body. In other words, even if the body is not involved in the realization of some cognitive explicit task, it is not a neutral factor of our understanding of why a system solves a task in (...) one way or another. Therefore, when conducting research on embodiment and the body’s cognitive system we should not neglect internal, cognitive processing. I appeal to Goldman’s research on embodied cognition to sketch the broader framework for internal processing in embodied cognition. I believe that even if we don’t accept Goldman’s approach as the viable proposal for embodied cognition in general, it’s a quite natural starting point for our analysis. Goldman (2012; 2014, and with de Vignemont 2009) argue for the essential role of the bodily formats or bodily codes (respectively: B-formats and B-codes) in embodied cognition. B-codes are here described as the processing of regions or sub-regions of the central nervous system. They are primarily employed for body control or monitoring, and reused for cognitive tasks. Beyond doubt, this conception provides an excellent starting point for analyzing the internal (mostly neural) processing in cases of embodied cognition. At the end of this paper, I will argue that the embodiment of cognition needs a conceptual twist. Following Keijzer’s (2015) interest in the evolution of the nervous system, and the minimal forms of cognition, I argue that in investigating embodied cognition, we should investigate the role played by cognitive processing for specific kinds of organisms, meaning organisms with a body of a particular morphology (size, shape, kinds, and distribution of sensors and effectors). Doing that, I refer to some conceptual and empirical considerations. I will also try to show that research on embodied cognition is still not sufficiently anchored in evolutionary and comparative studies on cognition, nor on the nervous system and body morphology. Bigger reliance on these kinds of studies, will make it make possible to gain a deeper understanding of internal processing in embodied cognition. (shrink)

In this article I will address the issue of the embodiment of computing systems from the point of view distinctive of the so-called Unconventional Computation, focusing on the paradigm known as Morphological Computation. As a first step, I will contextualize Morphological Computation within the disciplinary field of Embodied Artificial Intelligence: broadly conceived, Embodied Artificial Intelligence may be characterized as embracing both conventional and unconventional approaches to the artificial emulation of natural intelligence. Morphological Computation stands out from other paradigms of unconventional (...) Embodied Artificial Intelligence in that it discloses a new, closer kind of connection between embodiment and computation. I will further my investigation by briefly reviewing the state-of-the-art in Morphological Computation: attention will be given to a very recent trend, whose core concept is that of “organic reconfigurability”. In this direction, as a final step, two advanced cases of study of organic or living morphological computers will be presented and discussed. The prospect is to shed some light on our title question: what progress has been made in understanding the embodiment of computing systems? (shrink)