Biological Robots: Perspectives on an Emerging Interdisciplinary Field

Abstract

Advances in science and engineering often reveal the limitations of classical approaches initially used to understand, predict, and control phenomena. With progress, conceptual categories must often be re-evaluated to better track recently discovered invariants across disciplines. It is essential to refine frameworks and resolve conflicting boundaries between disciplines such that they better facilitate, not restrict, experimental approaches and capabilities. In this essay, we address specific questions and critiques which have arisen in response to our research program, which lies at the intersection of developmental biology, computer science, and robotics. In the context of biological machines and robots, we explore changes across concepts and previously distinct fields that are driven by recent advances in materials, information, and life sciences. Herein, each author provides their own perspective on the subject, framed by their own disciplinary training. We argue that as with computation, certain aspects of developmental biology and robotics are not tied to specific materials; rather, the consilience of these fields can help to shed light on issues of multiscale control, self-assembly, and relationships between form and function. We hope new fields can emerge as boundaries arising from technological limitations are overcome, furthering practical applications from regenerative medicine to useful synthetic living machines.

Classical Sorting Algorithms as a Model of Morphogenesis: self-sorting arrays reveal unexpected competencies in a minimal model of basal intelligence

“…Existing real-world biological examples of releasing sub-agents from explicit control, to ask what they would do if allowed, include the engineering of biobots. It has recently been shown that un-modified, genetically-normal cells self-assemble into constructs with novel behaviors when freed from the instructive influence of their neighbors (Blackiston et al, 2023;Gumuskaya et al, 2023), revealing baseline competencies not apparent from their standard role within default developmental algorithms. The minimal model shown here represents a first step toward the development of more general strategies to study emergent goals in collective systems and ways in which those goals cooperate with, compete with, and alter the performance of explicit goals we (or evolution) instantiate via hardware or software mechanisms.…”

Self-improvising Memory: a perspective on memories as agential, dynamically-reinterpreting cognitive glue

“…It cannot take for granted how much genetic material it will have [117], how many cells [120][121][122], or what size cells [116], it will have (in addition to any external damage it might sustain, or the chemical details of its environment -even the internal parts cannot be assumed to be the same as those with which its past genome was forged) 38 . Beyond the incredible robustness of standard form and function, we see adaptation to extreme changes of conditions, with no need for transgenes or genomic editing, in the spontaneous emergence of Xenobots [123][124][125], Anthrobots [126], and plant galls [127] (constructions of leaf cells hacked by signals from a non-human bioengineer to produce a totally new and complex pattern, Figure 5). This is also probably why chimerism and bioengineering, at all scales, workscoherent outcomes often result from combining not only divergent living components from different lineages [128] but also totally un-natural and novel engineered components, from nanomaterials to smart implants [129][130][131][132][133][134] (Figure 6).…”

Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue

“…It cannot take for granted how much genetic material it will have [143], or how many cells [146][147][148], or what size cells [142], it will have (in addition to any external damage it might sustain, or the chemical details of its environment-even the internal parts cannot be assumed to be the same as those with which its past genome was forged). Beyond the incredible robustness of standard form and function, we see adaptation to extreme changes of conditions, with no need for transgenes or genomic editing, in the spontaneous emergence of Xenobots [149][150][151], Anthrobots [152], and plant galls [153] (constructions of leaf cells hacked by signals from a non-human bioengineer to produce a totally new and complex pattern, as shown in Figure 5). This is also probably why chimerism and bioengineering, at all scales, work-coherent outcomes often result from combining not only divergent living components from different lineages [154] but also totally unnatural and novel engineered components, from nanomaterials to smart implants [155][156][157][158][159][160] (Figure 6).…”