Recent minimal modeling work, following a dynamical approach to the phenomenology of body memory and the en-active approach to cognitive science, has served as a computational proof of concept in support of conceiving body memory as a relational property that arises from the history of interactions of a whole brain-body-environment system, rather than as contents within the brain. Particularly, some of these studies have been focused on investigating the minimal type of social memory, i.e., dyadic body memory, using the so-called embodied dyadic interaction models. Here, we expand the related work on dyadic body memory by employing a sample of the embodied dyadic interaction models, which has demonstrated, in line with previous related work in social interaction, that by evolving agent pairs to maximize their neural complexity, they consistently display mutually coordinated behavior, which cannot be possible to achieve in isolation. We aim to investigate the emergent behavioral patterns during the encounters between agents with “different” (i.e., because of proceeding from interactive or isolated primary environments) minimal social ontogenies. For this purpose, we propose a re-definition of the concept of social ontogeny as the shaping of “being social”, which involves body memory, as being arisen from shared histories of social interactions, and present three simulation experiments. Our results revealed the emergence of three core behavioral patterns: (1) mutually coordinated dyads, (2) “exaggerated-shy” dyads, and (3) limited-coordination dyads. An analysis of agents’ neural and behavioral complexity is also performed. We then draw loose analogies between our findings and real-world examples.

To feed the growing human population we require increased food production and security, while using less land and causing less environmental damage. Significant changes in agriculture are needed to meet these demands. One widely touted solution is smart, Al-enhanced Agricultural Technology. In this article we argue that improved technology is insufficient to address the needs of many farmers, but that by taking a whole-of-system approach native to Artificial Life we can shift towards creating sustainable, ethical and effective AgTech. This can innovate industrial agriculture in developed nations and benefit small landholders from vulnerable communities, whilst reducing the environmental impacts of food production globally.

Cities are pervasive and they are some of the most powerful ecosystems of the Anthropocene. They have been around for almost 10000 years, and by the year 2050 most humans will be living in a city. Although it is known that cities have an impact to different scales, from the very local to the whole Earth System, its implications are far from being understood. Studying cities as organismic systems has been a productive strategy and favourable to complex adaptive systems analyses. However, the organismic view is to a great extent metaphorical, focusing exclusively on human activity, instead I argue for an approach that actually considers life processes as constitutive to them. In this extended abstract I suggest a conceptual framing for a synthetic approach to cities in which life processes are paramount for their understanding. Specifically, I will focus on two aspects: 1) the human-teleological component of cities and 2) the role of life processes organisationally closing the city, and bringing forth a self-generated unity and identity and the conditions for its own evolution. I believe that due to the increasing interest of the ALife community in tackling social issues, ALife unique insights and methods can be of great value in understanding cities and dealing with the social-ecological challenges they pose. A definition of cities from a synthetic perspective can help the ALife community to put into action its epistemic arsenal.