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We discuss the problem of assembling complex physical systems that are structured from the nanoscale up through the macroscale, and argue that embryological morphogenesis provides a good model of how this can be accomplished. Morphogenesis (whether natural or artificial) is an example of embodied computation, which exploits physical processes for computational ends, or performs computations for their physical effects. Examples of embodied computation in natural morphogenesis can be found at many levels, from allosteric proteins, which perform simple embodied computations, up through cells, which act to create tissues with specific patterns, compositions, and forms. We outline a notation for describing morphogenetic programs and illustrate its use with two examples: simple diffusion and the assembly of a simple spine with attachment points for legs. While much research remains to be done — at the simulation level before we attempt physical implementations — our results to date show how we may implement the fundamental processes of morphogenesis as a practical application of embodied computation at the nano- and microscale.

Historically cognition was understood as the result of processes occurring solely in the brain. Recently, however, cognitive scientists and philosophers studying "embodied" or "situated" cognition have begun emphasizing the role of the body and environment in which brains are situated, i.e. they view the brain as an "open system". However, these theorists frequently rely on dynamical systems which are traditionally viewed as closed systems. We address this tension by extending the framework of dynamical systems theory. We show how structures which appear in the state space of an embodied agent differ from those that appear in closed systems, and we show how these structures can be used to model representational processes in embodied agents. We focus on neural networks as models of embodied cognition.

Embodiment is a key to solving the reliability and alignment issues in the current AI. This is because it imposes consistent constraints on the entire agent-environment interactions and accompanying information without specifying their actual contents, and the constraints are common to those with similar embodiment. The concept of embodiment should be generalized beyond mechanical properties of the body and information structure of sensory signals, encompassing internal organs and metabolism, mental processes, and inter-agent interactions, to “super-embodiment”. It can address sensibilities, values and morals toward artificial humanity, which will be critically important for the next generation AI. [Y. Kuniyoshi, Open-ended intelligence arises from emergence and development from embodiment, J. Robotics Soc. Jpn. 41(7) (2023) 585–590 (in Japanese); Y. Kuniyoshi, Fusing autonomy and sociality via embodied emergence and development of behaviour and cognition from fetal period, Philos. Trans. R. Soc. B: Biol. Sci. 374 (2019) 20180031].

Collaborative robotics combines human and robot capabilities in shared workspaces, integrating robotics, human-computer interaction, ergonomics, and psychology. In industrial settings, human–robot collaboration typically involves physical interaction with collaborative robots (cobots), designed to assist in tasks such as manufacturing and logistics. However, we discuss that cognitive and social-affective layers of interaction are equally crucial for enhancing collaboration. By adopting the 4E-cognition framework, we argue that the concept of social embodiment, widely used in virtual agents and service robotics, could contribute to the design and implementation of industrial cobots. While socially relevant functions are often secondary to operational efficiency, integrating them into cobot design could enhance interaction quality, trust, and overall task performance. Focusing on cobots’ social presence and their ability to engage in proactive interactions can improve their acceptance and facilitate a sense of shared intentionality and agency in human operators. Finally, we discuss the ethical and practical challenges of developing socially embodied humanoid cobots, addressing the balance between cobot autonomy and human control, adaptive learning in long-term interaction and personalization, and the implications of building trust and transparency in human–robot collaboration. A more holistic design approach could yield both operational benefits and improved human well-being in collaborative environments.

The twenty-first century places new demands on student learning. New times call for new literacies. We witness keen interest in "serious games" and the use of games to enhance student learning. Against this backdrop, this paper examines issues related to bringing game-based learning into classrooms. It is argued that the construction of students' identity and sense of self are important but mostly overlooked educational goals. It is also noted that immersive games, by virtue of three associated learning characteristics—embodiment, embeddedness, and experience—are well-suited to supporting identity construction goals because they orient learning toward performance competencies that are intentional and possess a high degree of personal agency. We advocate a pedagogy that involves dialectic interplay between game-play experience and classroom-based discussion and reflection. These ideas are illustrated through a research project on National Education in Singapore. The game we have developed, Space Station Leonis, is a hybrid that comprises two modes of play: simulation mode and role playing scenario mode. We show how the game has been designed to help students develop a sense of who they are and what they stand for in a classroom learning environment that seeks to facilitate development of their identity in relation to being and becoming a Singapore citizen.

Machine consciousness is not only a technological challenge, but a new way to approach scientific and theoretical issues which have not yet received a satisfactory solution from AI and robotics. We outline the foundations and the objectives of machine consciousness from the standpoint of building a conscious robot.

Shanahan's eloquently argued version of the global workspace theory fits well into the emerging understanding of consciousness as a computational phenomenon. His disinclination toward metaphysics notwithstanding, Shanahan's book can also be seen as supportive of a particular metaphysical stance on consciousness — the computational identity theory.

There is an ongoing debate about the existence of humanoid robotics. The arguments tend to focus on the ethical claims that there is always deception involved. However, little attention has been paid to the ontological reasons that humanoid robotics are valuable in consciousness research. This paper examines the arguments and controversy around ethical rejection of humanoid robotics, while also summarizing some of the landscape of 4e cognition that highlights the ways our specific humanoid bodies in our specific cultural, social, and physical environments play an indispensable role in cognition, from conceptualization through communication. Ultimately, we argue that there is a compelling set of reasons to pursue humanoid robotics as a major research agenda in AI if the goal is to create an artificial conscious system that we will be able to both recognize as conscious and communicate with successfully.

For humans, phenomenal experiences take up a central role in their daily interaction with the world. In this paper, we argue in favor of shifting phenomenal experiences into the focus of cognitive systems research and development. Instead of aiming to make artificial systems feel in the same way humans do, we focus on the possibilities of engineering capacities that are functionally equivalent to phenomenal experiences. These capacities can provide a different quality of input, enabling a cognitive system to self-evaluate its state in the world more effectively and with more generality than current methods allow. We ground our general argument using the example of the sense of agency. At the same time, we reflect on the broader possibilities and benefits for artificial counterparts to human phenomenal experiences and provide suggestions regarding the implementation of functionally equivalent mechanisms.

We propose that examining the imagination through the eyes of an artist — the British Romantic poet/painter/engraver William Blake (1757–1827) — can provide fresh insights into the creative process of entrepreneuring. More specifically, we show how attempts to understand this process have been hobbled by assumptions handed down from the Enlightenment, or “Age of Reason,” the dominant paradigm of Blake’s time. Blake and other Romantic artists challenged these assumptions, expanding the boundaries of rationality to embrace unconscious, particularizing, embodied, and visionary modes of thought. In this essay, we explore the relevance of Blake’s holistic vision for the field of entrepreneurship — a vision that breaks with Enlightenment reasoning to embrace the fundamentally spiritual nature of reality; a vision that rejects institutionalized thinking to achieve social change through creative acts of the individual imagination, which Blake called the “Divine Imagination.” First, we outline Blake’s critique of Enlightenment assumptions about rationality that remain influential in entrepreneurship studies today, and show how Blake attempted to combat these assumptions by empowering the creative imagination to integrate and transform the fragmented human psyche. We then explore the implications of Blake’s vision for scholars who wish to more fully understand the role of the imagination in the process of entrepreneurial creation.

The discussion group focused on embodied processes in mathematics teaching and learning. At this discussion group, we aimed to consider the origins of movements performed by students, teachers, and artifacts. We invited group participants to reflect on resources initiating bodily movement and on the agents who perform or share the movement from a theory of dynamic systems, a new-materialist perspective, phenomenological perspective, embodied cognitive science, and cultural-historical approach. We questioned when and how movements become recognized as mathematical activity and discourse; we also discussed the criteria in prompting students to act or suspend enactment and leave room for imagination and articulating prediction of the enactment.

Preferring life to death is deeply rooted in our biology. With this study, we explored two questions: (1) Can this inclination be transposed to aesthetics so that a living being is valued as more beautiful than a non-living being? and (2) Are there any differences in the visual exploration of portrayals of a living compared to a dead human? In particular, are there any specific facial features representing the vitality status of a living or dead subject? By answering both questions, young adults’ eye gazing was analyzed while they observed, aesthetically judged, and judged the vitality status of faces extracted from paintings representing a sleeping or dead subject. The aesthetic preference for the stimuli as a function of vitality (living and dead) was assessed both during the eye-tracking study and during a follow-up priming behavioral experiment. The analysis of the responses given during the aesthetic judgment (AJ) task in the eye-tracking study revealed preference for the sleeping compared to the dead subjects, supporting proclivity to attribute greater aesthetic value to living beings. This evidence was substantially confirmed by the follow-up priming behavioral study, which further showed a significant effect of explicit vitality labeling on the aesthetic evaluation of the portrayals of sleeping subjects. As far as the visual exploration of the stimuli is concerned, the main eye-tracking results revealed great attention to the eye region of both sleeping and dead subjects, which was particularly enhanced for the sleeping compared to the dead subjects. For the latter stimuli, focused attention was also found in the mouth region. These results are discussed in light of different theoretical proposals, including the “embodied” theory of aesthetic perception based on the existence of mirror systems.

CBA is a six-layered architecture of consciousness linked to behavior such as reflex action, detour, and ambush. Two emotion-valued criteria are given for behavior selection. While a level of behavior is chosen to maximize the consciousness intensity, an action at the level chosen is selected to increase the pleasure. CBA is efficient for behavior selection because performing a complex task elevates the performer's level of consciousness. Inhibition of behavior triggers an elevation of the level of consciousness and behavior. The model design of detour and ambush was tested using two small mobile robots that had a limited temporal and spatial information of their environments. Emotion-valued criteria for behavior selection explain the meaning of behavior obstruction.

There are many facets to mental life and mental experience. In this chapter, I attempt to account for some central characteristics among those facets. I argue that normative function and representation are emergent in particular forms of the self-maintenance of far from thermodynamic equilibrium systems in their essential far-from-equilibrium conditions. The nature of representation that is thereby modeled — an interactive, pragmatic form — in turn, forces a number of additional properties of mental process, such as consciousness being inherently contentful and from a situated and embodied point of view. In addition, other properties of interactive representation make strong connections with the central nervous system properties that are found to realize mental experience, such as a field organization of oscillatory and mutually modulatory neural processes.

Soft robotics provides a new and exciting approach to design robots. Often inspired by the remarkable performances of biological systems a number of soft robotic designs have been proposed and implemented. Despite their great potential with respect to safety, energy efficiency, and adaptivity, soft robotics still faces a number of fundamental problems, e.g. their inherent complex dynamics that makes it difficult to apply classical control approaches. Morphological computation, a concept that understands that physical bodies can carry out computation, has the great potential to overcome this challenge by providing a novel point of view. Recent theoretical models on morphological computation as well real-world proof of concepts suggest that these unwanted complex dynamics of soft bodies can be actually beneficial and that they can be exploited as a computational resource. As a result, morphological computation allows to simplify the control and learning tasks by outsourcing computation to the physical body and, therefore, pointing to a potential solution for the control problem in soft robotics.