Programming the emergence in morphogenetically architected complex systems

Artificial Collective Intelligence Engineering: A Survey of Concepts and Perspectives

Collectiveness is an important property of many systems-both natural and artificial. By exploiting a large number of individuals, it is often possible to produce effects that go far beyond the capabilities of the smartest individuals or even to produce intelligent collective behavior out of not-so-intelligent individuals. Indeed, collective intelligence, namely, the capability of a group to act collectively in a seemingly intelligent way, is increasingly often a design goal of engineered computational systems-motivated by recent technoscientific trends like the Internet of Things, swarm robotics, and crowd computing, to name only a few. For several years, the collective intelligence observed in natural and artificial systems has served as a source of inspiration for engineering ideas, models, and mechanisms. Today, artificial and computational collective intelligence are recognized research topics, spanning various techniques, kinds of target systems, and application domains. However, there is still a lot of fragmentation in the research panorama of the topic within computer science, and the verticality of most communities and contributions makes it difficult to extract the core underlying ideas and frames of reference. The challenge is to identify, place in a common structure, and ultimately connect the different areas and methods addressing intelligent collectives. To address this gap, this article considers a set of broad scoping questions providing a map of collective intelligence research, mostly by the point of view of computer scientists and engineers. Accordingly, it covers preliminary notions, fundamental concepts, and the main research perspectives, identifying opportunities and challenges for researchers on artificial and computational collective intelligence engineering.

Morphogenetic metasurfaces: unlocking the potential of turing patterns

The reaction-diffusion principle imagined by Alan Turing in an attempt to explain the structuring of living organisms is leveraged in this work for the procedural synthesis of radiating metasurfaces. The adaptation of this morphogenesis technique ensures the growth of anisotropic cellular patterns automatically arranged to satisfy local electromagnetic constraints, facilitating the radiation of waves controlled in frequency, space, and polarization. Experimental validations of this method are presented, designing morphogenetic metasurfaces radiating far-field circularly polarized beams and generating a polarization-multiplexed hologram in the radiative near-field zone. The exploitation of morphogenesis-inspired models proves particularly well suited for solving generative design problems, converting global physical constraints into local interactions of simulated chemical reactants ensuring the emergence of self-organizing meta-atoms.

Multi-scale Chimerism: An experimental window on the algorithms of anatomical control

Despite the immense progress in genetics and cell biology, major knowledge gaps remain with respect to prediction and control of the global morphologies that will result from the cooperation of cells with known genomes. The understanding of cooperativity, competition, and synergy across diverse biological scales has been obscured by a focus on standard model systems that exhibit invariant species-specific anatomies. Morphogenesis of chimeric biological material is an especially instructive window on the control of biological growth and form because it emphasizes the need for prediction without reliance on familiar, standard outcomes. Here, we review an important and fascinating body of data from experiments utilizing DNA transfer, cell transplantation, organ grafting, and parabiosis. We suggest that these are all instances (at different levels of organization) of one general phenomenon: chimerism. Multi-scale chimeras are a powerful conceptual and experimental tool with which to probe the mapping between properties of components and large-scale anatomy: the laws of morphogenesis. The existing data and future advances in this field will impact not only the understanding of cooperation and the evolution of body forms, but also the design of strategies for system-level outcomes in regenerative medicine and swarm robotics.

Synthetic living machines: A new window on life

Increased control of biological growth and form is an essential gateway to transformative medical advances. Repairing of birth defects, restoring lost or damaged organs, normalizing tumors, all depend on understanding how cells cooperate to make specific, functional large-scale structures. Despite advances in molecular genetics, significant gaps remain in our understanding of the meso-scale rules of morphogenesis. An engineering approach to this problem is the creation of novel synthetic living forms, greatly extending available model systems beyond evolved plant and animal lineages. Here, we review recent advances in the emerging field of synthetic morphogenesis, the bioengineering of novel multicellular living bodies. Emphasizing emergent self-organization, tissue-level guided self-assembly, and active functionality, this work is the essential next generation of synthetic biology. Aside from useful living machines for specific functions, the rational design and analysis of new, coherent anatomies will greatly increase our understanding of foundational questions in evolutionary developmental and cell biology.

Life, death, and self: Fundamental questions of primitive cognition viewed through the lens of body plasticity and synthetic organisms

Central to the study of cognition is being able to specify the Subject that is making decisions and owning memories and preferences. However, all real cognitive agents are made of parts (such as brains made of cells). The integration of many active subunits into a coherent Self appearing at a larger scale of organization is one of the fundamental questions of evolutionary cognitive science. Typical biological model systems, whether basal or advanced, have a static anatomical structure which obscures important aspects of the mind-body relationship. Recent advances in bioengineering now make it possible to assemble, disassemble, and recombine biological structures at the cell, organ, and whole organism levels. Regenerative biology and controlled chimerism reveal that studies of cognition in intact, "standard", evolved animal bodies are just a narrow slice of a much bigger and as-yet largely unexplored reality: the incredible plasticity of dynamic morphogenesis of biological forms that house and support diverse types of cognition. The ability to produce living organisms in novel configurations makes clear that traditional concepts, such as body, organism, genetic lineage, death, and memory are not as well-defined as commonly thought, and need considerable revision to account for the possible spectrum of living entities. Here, I review fascinating examples of experimental biology illustrating that the boundaries demarcating somatic and cognitive Selves are fluid, providing an opportunity to sharpen inquiries about how evolution exploits physical forces for multi-scale cognition. Developmental (pre-neural) bioelectricity contributes a novel perspective on how the dynamic control of growth and form of the body evolved into sophisticated cognitive capabilities. Most importantly, the development of functional biobots - synthetic living machines with behavioral capacity - provides a roadmap for greatly expanding our understanding of the origin and capacities of cognition in all of its possible material implementations, especially those that emerge de novo, with no lengthy evolutionary history of matching behavioral programs to bodyplan. Viewing fundamental questions through the lens of new, constructed living forms will have diverse impacts, not only in basic evolutionary biology and cognitive science, but also in regenerative medicine of the brain and in artificial intelligence.

The body electric 2.0: recent advances in developmental bioelectricity for regenerative and synthetic bioengineering

Breakthroughs in biomedicine and synthetic bioengineering require predictive, rational control over anatomical structure and function. Recent successes in manipulating cellular and molecular hardware have not been matched by progress in understanding the patterning software implemented during embryogenesis and regeneration. A fundamental capability gap is driving desired changes in growth and form to address birth defects and traumatic injury. Here we review new tools, results, and conceptual advances in an exciting emerging field: endogenous non-neural bioelectric signaling, which enables cellular collectives to make global decisions and implement large-scale pattern homeostasis. Spatially distributed electric circuits regulate gene expression, organ morphogenesis, and body-wide axial patterning. Developmental bioelectricity facilitates the interface to organ-level modular control points that direct patterning in vivo. Cracking the bioelectric code will enable transformative progress in bioengineering and regenerative medicine.

Using synthetic biology to explore principles of development

Developmental biology is mainly analytical: researchers study embryos, suggest hypotheses and test them through experimental perturbation. From the results of many experiments, the community distils the principles thought to underlie embryogenesis. Verifying these principles, however, is a challenge. One promising approach is to use synthetic biology techniques to engineer simple genetic or cellular systems that follow these principles and to see whether they perform as expected. As I review here, this approach has already been used to test ideas of patterning, differentiation and morphogenesis. It is also being applied to evo-devo studies to explore alternative mechanisms of development and 'roads not taken' by natural evolution.

Diversity and survival of artificial lifeforms under sedimentation and random motion

Cellular automata are often used to explore the numerous possible scenarios of what could have occurred at the origins of life and before, during the prebiotic ages, when very simple molecules started to assemble and organise into larger catalytic or informative structures, or to simulate ecosystems. Artificial self-maintained spatial structures emerge in cellular automata and are often used to represent molecules or living organisms. They converge generally towards homogeneous stationary soups of still-life creatures. It is hard for an observer to believe they are similar to living systems, in particular because nothing is moving anymore within such simulated environments after few computation steps, because they present isotropic spatial organisation, because the diversity of self-maintained morphologies is poor, and because when stationary states are reached the creatures are immortal. Natural living systems, on the contrary, are composed of a high diversity of creatures in interaction having limited lifetimes and generally present a certain anisotropy of their spatial organisation, in particular frontiers and interfaces. In the present work, we propose that the presence of directional weak fields such as gravity may counter-balance the excess of mixing and disorder caused by Brownian motion and favour the appearance of specific regions, i.e. different strata or environmental layers, in which physical-chemical conditions favour the emergence and the survival of self-maintained spatial structures including living systems. We test this hypothesis by way of numerical simulations of a very simplified ecosystem model. We use the well-known Game of Life to which we add rules simulating both sedimentation forces and thermal agitation. We show that this leads to more active (vitality and biodiversity) and robust (survival) dynamics. This effectively suggests that coupling such physical processes to reactive systems allows the separation of environments into different milieux and could constitute a simple mechanism to form ecosystem frontiers or elementary interfaces that would protect and favour the development of fragile auto-poietic systems.