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Welcome to Evo-Devo Universe, the research community of the Evo-Devo Institute

Dear Scholars, Join Our Listserve!

Are you a scholar in complexity or adaptiveness, whether in cosmology, physics, chemistry, life sciences (evolutionary and developmental biology, cellular, organismic, and systems biology and ecology), mathematics, complexity science, network science, computer science, information theory, hierarchy theory, panarchy theory, resilience theory, systems theory, anthropology, psychology and behavioral science, ethics, complexity economics, political and social science, policy, engineering, urban studies, science and technology studies, history, philosophy, or any other complexity-related domain? Do you seek to better understand complex adaptive systems at all scales, including the universe itself, and the ways that adaptive systems manage the growth, partitioning, and life cycle of functional complexity under selection? If so, you've found a free, nonprofit-run, supportive international research community.

Scholars in this community recognize a fundamental dichotomy: some universal processes are perennially unpredictable (to local observers, at least) using indeterminacy, contingent generativity, and chaos in their dynamics, while others are intrinsically predictable both empirically and theoretically (with sufficient knowledge and simulation capacity), due to their special initial conditions (eg, conserved developmental genes in organisms, fine-tuned parameters in universes) and metastable environmental conditions (eg, physical laws and selection dynamics, in both organisms and universes). Life as a system clearly uses both processes, both explore (evo) and exploit (devo) adaptive strategies, at all scales, from Archaea to Earth's ecosystem. Many (not all) of us view adaptiveness in living systems as a set of algorithmic tradeoffs and tensions between exploratory, creative, contingent, unpredictable, and variational "evolutionary" processes, and exploitive, protective, conservative, predictable, replicative "developmental" processes, in any complex system under selection. This apparently universal evo-devo dynamic is particularly well studied at present in evo-devo biology and philosophy, but it can be generalized to any potentially autopoietic (self-maintaining, self-replicating, and creative) complex adaptive system under selection, at every scale of replication.

We also recognize that life creates not only niche-specific adaptiveness, which may increase or decrease functional complexity, but at the same time, in a subset of the network, we see increasing general adaptiveness (adaptive intelligence), systems that demonstrate an increasing capacity to simulate (learn) increasingly useful (pancontextual) aspects of their environment. Such systems can increasingly modify their environment to their purposes (niche construction), and persist in a growing variety of potential environmental conditions. Life, human-linguistic-technological co-evolution and culture, and associational, network-centric computation all exhibit growth in both niche-specific and general adaptive intelligence.

One of our community's research interests is to better characterize and understand network-centric and ecosystem processes that appear to direct and protect life's multi-billion year history of accelerating complexification. It is both a surprising and hopeful observation that the acceleration of structural and functional complexification since life emerged has been improbably and curiously smooth, at the network level, even through periodic catastrophes, both major and minor, when considered on planetary timescales. Many processes in biological dynamics become increasingly stable to catastrophe as their networks direct both local stochastic evolutionary search and global developmental optimization. A classic example is embryogenesis. Spontaneous abortions in human biology decrease from 40% in Week 1 to 0.1% in Week 42 of gestation, as increasingly complex networks emerge and stabilize the fetus. We may ask what latent forms of network learning and stabilization, may exist in cosmological evolutionary development. Network-centric processes may apply not only to the cosmos, but to all autopoietic systems, including human organizations and cultures. There is much potential human value in such research.

Scholars in our community discuss, debate, and publish on topics like evolutionary development (evo-devo) at all scales, dynamical systems theory, universal selection theory, multi-level selection, cosmological natural selection, universal fine tuning and the Standard Model of particle physics, cosmological learning theory, symmetry and gauge theory, quantum gravity hypotheses, nonequilibrium thermodynamics, dissipative systems, least action theory, network theory, active inference, information, meaning, learning, intelligence and computation theory, active inference theory, accelerating change, convergent evolution, teleonomy, Gaia theory, superorganism theory, and ethical, legal, economic, political, technological, and other forms of mental and behavioral individual and collective intelligence, including the study of our rapidly improving machine intelligence and ways that it may remain safe and generally adaptive.

Many of these topics are insufficiently accounted for in our (now very old and substrate-specific) gene- and organismic-centric Modern Synthesis of evolution, both in living systems and in multi-level selection theory. We are hopeful that studies in complexity science may lead us to a new Extended Evolutionary Synthesis, a universal selection theory that accounts for our cosmic and planetary history of accelerating complexification, that gives us deeper context for understanding perennially emergent opportunities and risks. We seek to step towards a set of models and insights that suggest how opportunities and risks may be better managed by adaptive and intelligent systems at all scales. Many of us are concerned about all the ways humanity's growing general, network-centric adaptiveness can fail, or create new risks and threats, in our rapidly-changing modern societies. We seek to use complexity and adaptiveness studies, and universal selection theory, not only to better understand our place in the universe, but to better manage and protect our teams, organizations, societies, and ecosystems against failure, risks, and threats, with more biologically-informed and complexity-aware models, strategies, polices, plans, actions, and reviews.

If any of this rings true to you, welcome! We are a community created in 2008 to support this kind of thinking and scholarship, still underappreciated in standard scientific culture today. Please consider joining our moderated and constructive listserve, EDU-Talk, where you can share your and others work, insights, and questions, and engage in moderated, evidence-informed discussion of these topics. We have roughly 120 scholars on the listserve at present, and we engage in regular formal virtual talks and lively informal discussions on any of the above topics.

To join EDU-Talk, you must have published at least one substantial article on any of the above or other complexity or adaptiveness-related topics. Non-peer-reviewed web publications are acceptable, if they meet a quality threshold in the judgment of the listserve moderators. Those with university and institutional affiliations are our primary membership. We welcome independent scholars, but we maintain a ratio of at least 50% institutionally-affiliated scholars, as our charitable purpose is to improve institutionally-generated scholarship, strategy, and policy in these topics.

What is Evo-Devo?

Evo-devo is a subfield of genetics, applied and theoretical biology, complexity science, and philosophy, first emerging in the 1990s, that explores how cyclic developmental processes direct, regulate, and constrain evolutionary change in autopoietic (self-maintaining, self-replicating, and creative) complex adaptive systems. Perhaps no one explains evo-devo genetics and dynamics better and faster than in this fun 4-minute music video, Evo-Devo, by Tim Blais of A Capella Science.

To be most accurate, this field might be called "devo-evo", considering developmental self-maintenance, hierarchy, modularity, and self-replication first in our theory, and evolutionary variation as logically secondary, as processes of variation are theoretically constrained by the needs of the developmental life cycle for viability. Leading scholars in evo-devo biology, including Brian K. Hall and Gunther Wagner, argued as much in 2000. But inertia had grown by then, and we are stuck with the name that emerged at the field's birth circa 1990.

A good case that development drives evolutionary variation, and not the reverse, is found in Evolution Evolving, 2024 by Kevin N. Lala (prev. Laland) (St. Andrews, niche construction and cultural learning), Tobias Uller (Lund, evo-devo), Nathalie Feiner (Max Planck, developmental genetics), Marcus Feldman (Stanford, gene-culture coevolution/dual-inheritance theory) and Scott F. Gilbert (Swarthmore, developmental biology and symbiogenesis). These scholars have elaborated a version of the Extended Evolutionary Synthesis (EES) in which development of phenotype is the primary unit of selection, with developmental mechanisms constraining the evolutionary variation that is possible in each system. The standard Modern Synthesis has selection acting on random genetic variation, with development as a passive conduit of genes. Their EES flips this view, proposing a model in which developmental processes accretively structure and bias the types of evolutionary variation that are possible. Natural selection thus acts simultaneously on both developmental (predictable) and evolutionary (variational) mechanisms. In this view, the genome is less a controller than it is a reactive network, responding to its environment increasingly in realtime, via genetic, epigenetic, behavioral, cultural-memetic, and ecological networks. Though they might or might not advocate for it, their model offers a way for complexity scholars to explore the idea of predictable and hierarchical macroevolutionary development (high-probability major evolutionary transitions as complexity attractors on all Earth-like planets) as well as the hypothesis of convergent cosmic development, the proposal that there are in-principle predictable physical, chemical, biological, cultural, and technological processes and complexity emergences occuring in parallel in our universe, processes we can increasingly model and simulate as we learn more of the falsifiable evo-devo dynamics of life on Earth.

Evo-devo biology tells us that both developmental and evolutionary processes are fundamental to living systems. Importantly for theory, they can each be empirically defined to have two different and partly oppositional adaptive purposes and dynamics.

In information theory, we might define developmental processes as any that conserve previously acquired information that causes future predictable, hierarchical emergence, life cycle, and replication under selection. Evolutionary processes, by contrast, might be defined as any that create new information, in future unpredictable, recombinant and contingent ways. Both processes involve inheritance parameters and the exploitation of regimes of predictable and unpredictable physics, and both are subject to selection in the environment.

In physical dynamics, we see that evolutionary processes create novel structure and function in primarily bottom-up, local, creative, divergent, and increasingly future-unpredictable ways, while developmental processes conserve critical structure and function in top-down, global, conservative, convergent and future-predictable ways. We can discern the holistic and deep-future predictable nature of developmental processes either via empirical observation of any autopoietic system over its life cycle (e.g., a seed of a particular species becoming an organism with a particular phenotype) via long-term surveys of ecosystems (e.g., convergent evolution of species types on different continents) and occasionally, via causal computational simulation (e.g., Eric Davidson's models of gene regulatory network dynamics in sea urchin development). Both developmental and evolutionary processes are fundamental contributors to adaptiveness in any autopoietic system under selection.

Perhaps the most foundational insight from evo-devo theory in biology is that we should strive to deeply understand development first, as the capacity for an autopoietic system to use local chaos and contingency to reliably and robustly produce a predictable, hierarchical series of spatially- and temporally-specific future global emergences, across self-maintaining replicative cycles. In genetics, a subset of parameters (eg, the developmental genetic toolkit) are both highly conserved and finely tuned, while the remaining "evolutionary" parameters are free to vary.

In the evo-devo universe hypothesis (see Lee Smolin's Cosmological Natural Selection for the most-studied variant), a similar fine-tuning condition has been (partially) simulated with respect to the 31 (by current count) fundamental parameters of physics and cosmology. Only a subset may be fine-tuned, via self-organization, for the stability of the universal life cycle and its intrinsic learning capacity. Such fine-tuning would naturally emerge within initially random fundamental cosmological parametric networks if the replicator is capable of duplication (creating a randomizing population) and if the parametric intelligence they encode has any nonrandom value to the replication cycle, under selection. This is the same claim made in evo-devo genetics for the nonrandom and accretive emergence of network intelligence in all living replicators, beginning with prebiotic chemical networks. In many origin of life models, evolutionary processes can be considered as an emergent overlay on self-organizing and self-maintaining developmental (replicative and self-maintaining) processes, offering adaptive advantage by creating greater population and network diversity, and iteratively feeding new weights and parameters into coordinating networks. Again, in living systems, this accretion must occur in carefully constrained ways, ways that do not disrupt life-critical developmental dynamics.

Universal Selection Theory (UST), also called Universal Darwinism (UD), is the idea that inherited parameters, replicating and varying under selection, are at the center of learning and adaptiveness in all complex systems, from quantum physics to chemistry to life to nervous systems to human culture to technology to the universe itself. Evo-devo systems theory (EDST) is a variation of UST that seeks insights from evo-devo biology, to better understand selection and adaptation in all autopoietic (self-maintaining, self-replicating, and self-varying) systems. It reminds us that evolutionary and developmental processes are partly oppositional in their informational and physical dynamics, and that adaptive networks, and network science, are at the center of evo-devo processes. It is both the self-organizing conservative and exploratory properties of networks of genes, gene products, switches, circuits, modules, phenotypes, and species that create life's stunning complexity, predictability, persistence, creativity, and adaptiveness. Evo-devo network models promise to help us understand why life itself, a single autopoietic and interdependent genetic regulatory network, has been so amazingly diverse, complex, hormetic (adding new capability and complexity under right-sized stress), persistent (3.5 Billion years and counting), and adaptive, by comparison to all of its species and individuals. It has always been networks, not species or individuals, that have been the greatest adaptors in complex systems.

At present, it is our research community's majority (but neither exclusive or proven) view that such dyadic processes as robustness/evolvability, exploit/explore, efficiency/plasticity, determined/indetermined, predictable/unpredictable, convergence/divergence, criticism/conjecture, falsification/hypothesis, centralize/decentralize, integration/segregation, cooperation/competition, protect/create, stability/transcendence, development/evolutionary search are also teleonomies (entrained goals) being balanced by agentic networks in all autopoietic systems. Which process is favored under selection will be dependent on diverse agentic and environmental contexts. But the categories themselves may be plausibly based on the partially predictable, largely unpredictable nature of the universe itself. Working with the insights of Ilya Prigogine on dissipative adaptation, and Maturana and Varela in autopoiesis, the systems theorist Erich Jantsch inspired many integative thinkers with an early view of cosmic self-organization in his book The Self-Organizing Universe (1980), treating all adaptive systems in a tension between self-stability and self-transcendence. Such synthetic work is far from finished, and our community is dedicated to exploring both its value and deficiencies.

To sum up, the self-organizing, network-centric, autopoietic (evo-devo) view of complex adaptiveness may be truly foundational. Our community was formed to investigate this view. We seek to better define and understand evo-devo processes in life and intelligence, and in all of its other replicating and varying partners, including human language, ideas, behaviors, laws, institutions, organizations, and technologies. Most promisingly for theoretical grounding, evo-devo dynamics may even be key to the deepest understanding of our universe itself, if it is also a self-replicating and self-organizing system with both a finite individual lifespan and a perpetual life cycle, as models like Cosmological Natural Selection and more recent models of Cosmological Learning propose. If all adaptive systems within our universe are autopoietic systems, it does seem conceptually parsimonious to many of us that universal complexity itself has self-organized, under selection, via the same evo-devo dynamics that we find in all replicating intrauniversal systems, from suns to molecules to life, to intelligent life, and to what may come next.

What is Accelerationology?

Accelerationology (acceleration studies) is the nascent scientific study of physical and informational forces, processes and models of accelerating complexity emergence. It is not accelerationism, the blind faith in plutocratic libertarian capitalism and disruptive change recently championed by some of our tech elites. It is instead a humble attempt to understand accelerating processes in complex systems, and to develop better models, policies and processes for regulating them in service to ecosystem adaptiveness. The universal acceleration of complexity is a poorly funded and understudied topic in science, and our community has adopted it as one of our research areas.

Gravitation is a force that has played a key ordering role in the emergence of stellar and geocomplexity. Life's major evolutionary transitions, guided by molecular inheritance systems, have been accelerative by various definitions of structural and functional complexity. Human symbolic emergence and inheritance has been profoundly accelerative of mental, social and physical complexity production. Since the birth of science, informational and computational production, inheritance, variation and selection have been profoundly accelerative. Our universe exhibits continually accelerating complexification in a small subset of its processes and domains. Agency grows, and a subset of systems exhibit increasingly general niche-constructing intelligence.

It has not always been so. As Robert Aunger (Aunger 2007) and others observe, from the beginning of the universe until the emergence of life, we see a coarsely decelerative pattern of complexity transitions. Our universe began with quark confinement in the first microseconds, accomplished nuclosynthesis in the first minutes, then recombination (transparency) over ~300,000 years. Constructing the first stars (and supermassive black holes) needed ~100 million years. The first galaxies and large scale structure, ~1 billion years. Expansion and cooling drove this global slowdown in transitions. Curiously, we see an analogous global deceleration, also for energetic reasons, in complexity production in the early embryo. At the same time, Eric Chaisson and others have modeled an increasingly local acceleration of free energy flow density (per mass and volume) in a subset of dissipative systems, beginning with the emergence of the first galaxies, even as universal complexity transitions decelerated. This growth in energy flow density is proposed to be driven via some combination of gravitation and "metabolic" complexification (Chaisson 2001; Penrose 2004).

Here on Earth, with the beginning of life and its inheritance mechanisms, both global complexity transitions and local energy-flow densities have accelerated in tandem. Life's global energetic and structural acceleration are debatable at first: paleobiologists estimate 1.5 billion years for the transition from Archea to cyanobacteria, 1 billion years to eukaryotes, then a "boring billion" (1-1.5 billion years) for biological events in the Mesoproterozoic era before Ediacarans (the first known large multicellular animals with diverse body types) 575 mya. Recent research argues that this pre-Ediacarian era was accelerative in genetic, biogeochemical, and tectonic processes (though it remains contested). We still have serious deficiencies in our models of molecular and cellular complexity transitions. But from Ediacarans to the present, the accelerative pattern is quite robust. The astronomer Carl Sagan popularized this universal pattern in his Cosmic Calendar metaphor. He proposed it in 1977 as a phenomenon worthy of scientific study. We named the field accelerationology, and have been exploring it since the founding of our institute in 2008.

This topic remains niche today, yet some progress has been made. Accelerating change is longer dismissed as an artifact of poor data, or as a misleading heuristic of human perception. The usefulness of logarithmic time in describing big history, for example, does not apply to human life history, where early events are typically better remembered (recency bias). Certainly the complexity transitions and systems chosen in periodization models greatly influence the patterns observed, and can be arbitrary. We must guard against arbitrariness, motivated reasoning and confirmation bias, and test many definitions of system boundaries, complexity, and complexity transitions in an attempt to more rigorously periodize change. Yet dozens of scholars, using a wide range of models, have observed the structural and functional acceleration of life, human culture, and technology on Earth. It has some basis in reality.

All of these scholars have wondered where and when it exists, what produces it, what stabilizes it, what function it may serve, and where it may lead. Answers to such questions are today quite speculative, yet we would argue they are also quite important to our understanding of universal dynamics. Within the last few centuries, humans have noticed acceleration over their lifetimes. With the emergence of mass use of deep learning AI since 2023, it is more noticeable today than ever. We live it daily, at present.

There are several physical and informational theories for the generation of cosmic complexity. Perhaps the most grounded is the law of least action, applied to both physical and informational (computational, cognitive) systems (Georgiev 2002). Least action has been used in promising models including active inference, proposing that neural (and cultural and technological) systems engage in free energy minimization in predictive processing (Friston et al 2022) via perception-action cycles. Such "prediction" under selection for active persistence may arise even in the simplest chemical networks (Kauffman 1991) and physical networks (Rovelli 1996). Some models of computational complexity growth also involve a growing resource-independence for autopoietic systems, as they progressively miniaturize, localize, digitize, and virtualize their metabolic and computational architectures (Smart 2012). In the history of computing, each computational paradigm experiences logistic performance growth, initially exponential, then saturating. But there is also a second order exponential (or superexponential) curve for the most complex actors in the ecosystem that demonstrates successive complexity transitions to increasingly resource-efficient and computationally-dense architectures (Kurzweil 2005). Some scholars have proposed that the limit of such efficiency and density acceleration is reached at black hole densities (Barrow 1998; Lloyd 2000). Curiously also, after billions of years of deceleration, spacetime itself began accelerating ~7 bya under dark energy.

There are also some theories for what protects this acceleration. A type of network robustness appears to be involved. With sufficient network redundancy and diversity, a handful of scholars have observed that catastrophes cause a hormetic effect strengthening phylogenetic, ecological and social networks after catastrophe (Holling 2001; Homer-Dixon 2006; Taleb 2012). Is the massively parallel nature of our universe a protection against Great Filters (Hanson 1996) that frequently arise due to evolutionary randomness in cosmic complexification? Or is our universe itself developmental, with emergent networks stabilizing major complexity transitions, making them more protected and symbiogenic after each transition (Margulis 1998; Smart 2019; Aguera y Arcas 2025)? Such questions, unclear as they are today, are nevertheless of vital importance to our future.

There are even theories for why acceleration might exist functionally for the universe as a system. Some involve a variant of least action efficiencies in universe reproduction. From an evo-devo lens, there is much to explore. Positive feedback loops in biology are necessary for any decision that must stay made. They are a hallmark of irreversibility in emergence. We find them in cell fate commitment in development, in apoptosis, in immune activation, in the buildup of molecular messengers Cdk1–Cdc25–Wee1 prior to mitosis and meiosis, in the LH surge in ovulation, in sperm capacitation, in the acrosome reaction, in fertilization, in birth (the Ferguson reflex), in sexual maturation (to a threshold), and in the action potential and in synaptic plasticity. When we shift from molecular to organism scale, the physiologist Arthur Guyton observed thatreproduction tops the list of positive feedback neuroendocrine mechanisms that are not pathological (Guyton 1956). Clotting, the action potential, and synaptic plasticity (the latter supporting computation as a function) being the other notable accelerations-to-emergence at the organism scale. It is in reproduction and learning that we find these one-way commitment processes unusually coordinated across biological scales.

Such observations allow us to propose a functional hypothesis that is both speculative yet also groundable in autopoietic complexity theory. If our universe is both a finite system, with a beginning and end, and also a replicator, as is proposed in cosmological natural selection, and if emergent network intelligence is nonrandomly useful to our universe's persistence, or its adaptation in whatever unknown environment it is embedded within, then it is plausible that irreversible complexity development accelerates with life and its progeny because intelligence serves a an adaptive function in universe reproduction. This intelligence function might first emerge with the simple act of random parameter variation in universe reproduction, as the cosmologist Lee Smolin proposes. If such parameters explore a network phase space under autopoiesis and selection, the way gene networks do, they could lead naturally to universes where our kind of higher intelligence would eventually emerge and be able to influence our universe's reproduction, the way all intelligent organisms do via their own agency and choices. The cosmologist Edward Harrison (Harrison 1995) was the first to make such a proposal, to our knowledge. Others in our community have continued research on this reproductive acceleration hypothesis (Smart 2012; Vidal 2014; Price 2018; Gough 2025).

Unfortunately, too little attention and funds have been dedicated to accelerationology since it was proposed as a research domain by 20th century scholars (Piel 1972; Sagan 1977) for us to have good answers to these and other questions. Yet the study of accelerating change, where and when it exists in our universe, what drives it, what protects it, and what adaptive functions it may serve, is a key research interest for our community. As deep learning AI exhibits a native learning rate that is at least six orders of magnitude faster than the action potentials in biological brains, we would argue that understanding and regulating acceleration dynamics in our digital ecosystems is a topic that has become important to the future of humanity.

We suspect that accelerating change signifies something deep with respect to what will be needed to explain adaptiveness in complex systems. Some kind of least action, inheritance accumulating, predictive, protective, positive-feedback, resource-densifying component must be added to autopoietic (evo-devo), network-centric models if we are to understand accelerating adaptiveness. Perhaps some variant of the reproductive acceleration hypothesis may be made more predictive and falsifiable. Or perhaps, as Santa Fe Institute scholar David Krakauer argues, there are multi-way tensions that are more fundamental than the devo/evo, predictable/unpredictable dynamic, such as speed/accuracy/robustness/evolvability as a four-factor model. We make no claim to any definitive answers to these questions, only that we consider them fundamental to the search to better understanding of both our complex universe and human adaptiveness in a world of accelerating change.

Evo-Devo Exemplars

If the multiscale evo-devo model is a "less wrong" representation of reality than our current paradigms, we should be able to find consilient exemplars in many scientific domains. Below are a sample of scholars whose work is deeply consilient with a dual-category, network-centric evo-devo approach to physical, informational, and adaptive dynamics. The six research areas listed below are a simplification of the research questions and scientific domains explored in our community. Disclaimer: Most of these scholars are not presently affiliated with our research community, and they may or may not agree with our epistemic framing and assumptions.

Complexity - Multiscale, Network, and Evo-Devo Complexity Science

Stuart Kauffman (formerly at the Santa Fe Institute) in Investigations (2000) and A World Beyond Physics (2019), explores the model that biological evolution perpetually creates new phase space that cannot be prestated or predicted. His concept of the adjacent possible models how combinatorial exploration generates unpredictable novelty via new phase space production. His NK model for network connectivity and configuration phase space shows that overconnected systems (high K) get stuck on local peaks (overexploitation) while underconnected systems (low K) explore too randomly. In Kauffman's view, the universe is not mathematically closed, and agency emerges directly from computational incompleteness. It is an adaptive property of sufficiently complex systems, emerging incrementally from the predictable/unpredictable dynamics of the simplest autopoetic replicators. With Andrea Roli he proposes molecular reproduction is a first-order phase transition that must arise from sufficiently complex prebiotic chemical networks (Kauffman and Roli 2024).

David Wolpert at the Santa Fe Institute explores the fundamental limits of prediction and computation in physical systems, including thermodynamic limits on inference and the mathematics of what cannot be known. His No Free Lunch theorems in optimization and learning, co-developed with William Macready, formalize why no single search or learning strategy, for any agent, can dominate in all possible environments. Wolpert also explores the thermodynamics of agency and the bounds of what agents can know (predict) about the world.

Nigel Goldenfeld at UC San Diego has worked extensively on the boundary between predictable (developmental) and unpredictable (evolutionary) dynamics, in both physical and biological contexts. In collaboration with Carl Woese, the discoverer of Archaea (the third domain of life), he proposed that life's earliest stages operated as a communal network of genetic exchange long before LUCA (the first cell). In Life is physics (2010) both argue that evolution cannot be explained solely by population genetics, but is fundamentally a far-from-equilibrium system driven by both physical and informational dynamics.

Jessica Flack at the Santa Fe Institute has explored how complex systems use microscopic stochasticity (evolutionary search) to produce macroscopic regularity. In her coarse graining model, she argues that the components of many adaptive systems collectively compute their macroscopic worlds in a process of downward causation. She argues that stronger forms of downward causation play an agency role in the production of new organizational levels. In this 2017 paper, she explores such processes in biology, in social systems, and in artificial neural networks.

Eric J. Chaisson, Harvard University has proposed a single quantitative metric for cosmic evolution: energy rate density, Φ_m, the free energy flowing through a system per unit mass per unit time (erg s⁻¹ g⁻¹). Rooted in the thermodynamics of dissipative structures, Φ_m rises along a near-monotonic ladder in "leading" complex systems across cosmic history — galaxies ~0.5, stars ~2, planets ~75, plants ~900, animals ~20,000, brains ~10⁵, human culture ~500,000, and modern computing substrates (orders of magnitude higher). Chaisson's key works are Cosmic Evolution: The Rise of Complexity in Nature (2001) and the two-part "Energy Rate Density" papers (Complexity, 2011). The metric is not perfect. There are a handful of structures and processes with high Phi that are not obviously adaptively complex. Explosions, jet engines, etc. Yet for the major transitions in complexity in both cosmic and evolutionary history, Phi is useful as thermodynamic correlate of complexity. As a metric of "metabolism" of complex systems, and perhaps an indirect measure of their computational capacity, it is fascinating that this metric accelerates over cosmic time in more recent systems. Normalized to mass, a Sunflower's free energy throughput profoundly dwarfs the Sun's luminosity per gram.

Physics - Quantum, Thermodynamics, Cosmology, Earth Sciences, and OOL

John Sutherland et al. (Nature Chemistry, 2015) showed that hydrogen cyanide, hydrogen sulfide, and UV light can simultaneously generate precursors to nucleotides, amino acids, and lipids — all three major biomolecular classes from a single simple early Earth chemistry. This directly undermines the argument that these classes of molecules require separate, improbable coincidences.

Nick Lane and Mike Russell's work on alkaline undersea hydrothermal vents proposes that proton gradients at vent mineral interfaces chemiosmotically drove early metabolism. They propose the thermodynamic engine of life was geologically developmental (statistically highly probable) on planets like ours. This view is consistent with the observation that life emerged on Earth within just a few hundred million years of the persistence of surface water.

Jeremy England (formerly MIT Physics of Living Systems) proposes dissipative adaptation as a thermodynamic process that raises the probability of durable emergent life-like structure prior to and independent of the emergence of molecular heredity. In "Statistical Physics of Self-Replication" (J. Chem. Phys. 2013) he derives a lower bound linking a replicator's heat dissipation to its growth rate, internal entropy, and durability. In "Dissipative Adaptation in Driven Self-Assembly" (Nature Nanotechnology 2015) and Statistical Physics of Adaptation (with Perunov and Marsland, Phys. Rev. X 2016) he generalizes the mechanism to many-body systems. His trade book Every Life Is on Fire (2020) frames far-from-equilibrium thermodynamics as one pillar of a developmental route to the origin of life, continuing the dissipative self-organization work of Ilya Prigogine and colleagues.

Terrence Deacon (UC Berkeley) is a biological anthropologist and neuroscientist whose work gives the EDU framework a thermodynamically grounded account of how end-directed, self-maintaining organization — the precondition for both development and selection — can arise from ordinary physical dynamics. He proposes the autogen (a minimal self-repairing, self-reproducing system that appears when two individually self-limiting self-organizing processes — autocatalysis, which generates catalysts, and self-assembly, which generates a containing shell — are reciprocally coupled so that each produces the boundary conditions the other needs, driving the pair toward a self-sustaining state neither could reach alone). Introduced in "Reciprocal Linkage between Self-organizing Processes Is Sufficient for Self-reproduction and Evolvability", Biological Theory, 2006 and developed in Incomplete Nature: How Mind Emerged from Matter (Norton, 2011), the autogen proposes a three-tier emergence hierarchy: homeodynamics (entropy-increasing thermodynamics), morphodynamics (order-generating self-organization — dissipative structures, autocatalytic sets), and teleodynamics (genuine end-directedness emerging when morphodynamic processes are mutually entrained). His earlier The Symbolic Species (Norton, 1997) supplies a complementary evo-devo thesis — the Baldwinian coevolution of language and brain via niche construction and developmental plasticity. His work on relaxed selection, "A role for relaxed selection in the evolution of the language capacity," PNAS 2010, argues that the loss or delay of developmental constraint, not only its imposition, can drive increases in biological complexity. Two examples of this in biology are developmental heterochrony and specifically, neoteny in which time-dependent delay of effects of the developmental genetic network, creates less-developed offspring. We see this effect in humans with delayed prefrontal cortex and synaptic development (Somel et al. PNAS 106, 2009; Petanjek et al. PNAS 108, 2011) and with self-domestication for prosociality (Wilkins, Wrangham & Fitch, Genetics 197, 2014; Hare, "Survival of the Friendliest," Annu. Rev. Psychol., 2017) both of which afford humans powerful new cultural evolutionary capacity.

Lee Smolin (Perimeter Institute) originated cosmological natural selection (CNS), the proposal that universes reproduce through black holes, in a "bounce" to new universe production rather than a singularity, with each offspring inheriting slightly "mutated" fundamental constants, so that constants tuned to fecund black-hole production come to dominate the multiverse population. Smolin's trade book The Life of the Cosmos (1997) offers a physical-informational model of a universe subject to variation, inheritance, and (some form of) selection, and an analog to a cosmic germline. In "Precedence and freedom in quantum physics," arXiv:1205.3707, 2012, Time Reborn (2013) and The Singular Universe and the Reality of Time (with Roberto Unger, 2015) he argues that physical laws are not fixed but evolve as "habits" within universal history (his "principle of precedence"). More recently, he coauthored "The Autodidactic Universe" (2021) and related cosmological learning (CL) work, which attempts to bring learning and intelligence into the replication cycle. If CNS is based on blind variation and selection, CL assumes that universal intelligence, which is never omnicient or omnipotent, emerges within the replicator to make its variation "less blind".

Stephon Alexander (Brown University) is the lead author of The Autodidactic Universe (2021, with Cunningham, Lanier, Smolin, and others), proposing that the universe learns its own physical laws by exploring a landscape of candidate laws expressed as matrix models, which the authors map onto both gauge/gravity theories and to unsupervised learning machines such as recurrent neural networks, so that the evolution of law is formally analogous to a network training run. A theoretical physicist working on inflation, dark energy, and the interface of particle cosmology and quantum gravity, Alexander's books The Jazz of Physics (2016) and Fear of a Black Universe (2021) develop the theme of the cosmos as a generative, self-organizing system. His work is consilient with EDU's exploration of the universe as an autopoietic system whose regularities self-organize under selection.

Bio - Evolutionary, Developmental, Ecological, and Systems Biology

Günter Wagner at Yale is a rigorous theoretical evo-devo biologist. His work on robustness (predictable ergodicity and canalization) and evolvability (unpredictable and generative search), explores how developmental systems are simultaneously conservative (buffering against mutation) and creative (natively evolving and experimenting). His book Homology, Genes, and Evolutionary Innovation (2014) is perhaps the most technically sophisticated treatment available today of how developmental constraint and evolutionary exploration interact in agentic systems at all scales of living complexity.

Andreas Wagner at University of Zurich (doctoral student under Günter, but no familial relation) has done extensive work on the genotype-phenotype map, how genetic systems navigate phenotype space. His technical book, Robustness and Evolvability in Living Systems (2013) and his trade book, Arrival of the Fittest: How Nature Innovates (2015) both explore how developmental robustness and evolutionary evolvability are deeply linked through the topology of neutral networks--vast, mutationally robust webs of different genetic sequences that reliably produce (develop) the same physical trait.

Marc Kirschner (Harvard Medical School) and John Gerhart (UC Berkeley) developed the theory of facilitated variation, which claims that phenotypic variation is disproportionately viable and functional because a conserved developmental toolkit has self-organized to absorb genetic change and convert it into coordinated, workable phenotypes. In The Plausibility of Life (Yale, 2005), and in PNAS 104, 2007), the theory proposes a small set of conserved core processes — the genetic code, metabolism, the cytoskeleton, membrane and signaling pathways (Wnt, Hedgehog, Notch, TGF-β, RTK), and the Hox axial-patterning system have barely changed in evolutionary history, versus a vastly larger regulatory periphery (largely cis-regulatory DNA) where almost all evolutionarily relevant variation occurs. Evolution proceeds mostly by re-deploying the ancient cores in new times, places, and amounts (developmental heterochrony) rather than by inventing new core machinery. Three design features of the cores make this work: weak regulatory linkage (a signal merely triggers or de-represses a response the cell already knows how to make), compartmentation/modularity (components can be re-regulated independently), and exploratory behavior (cores that generate a large excess of variant states and then stabilize the functional ones by selection). This model maps well to an evo-devo dyad: the conserved cores are the constrained, robust, "exploit" pole, deeply canalized and reused (Waddington 1942); the regulatory periphery is the stochastic, "explore" pole that generates diversity. They offer the exploratory growth of microtubules/cytoskeleton, connections in the developing brain, the vascular system, muscle-tendon-nerve development, and the adaptive immune system. This model maps well to the 95/5 Rule (Smart 2019). This work is consilient with other scholars of the Extended Evolutionary Synthesis (EES), including Gunter Wagner and Lee Altenberg's work on evolvability and modularity (Evolution, 1996), Mary Jane West-Eberhard's Developmental Plasticity and Evolution (2003), and Andreas Wagner's work on the robustness of developmental networks to random genetic change (Arrival of the Fittest, 2014).

Eva Jablonka (Tel Aviv U) and Marion Lamb (U London) cowrote Evolution in Four Dimensions (2005) a foundational evo-devo text that argued for genetic, epigenetic, behavioral, and symbolic evo-devo inheritance systems, each operating at different timescales and with different predictability and agency profiles. Jablonka's work on multiscale, multisystem learning as an evolutionary mechanism connects directly to predictive processing as a framework for managing persistent unpredictability.

Denis Noble at Oxford is a leading critic of overly gene-centric biology and advocate of multi-level selection in evolution. His concept of biological relativity, outlined in Dance to the Tune of Life (2017), proposes that there is no privileged causation level in biological systems. He argues that predictability depends entirely on the system, scope, and timescale of observation. As in physical relativity, the dynamics observed depend on the context of the observer. His work with the Third Way of Evolution group is one of several efforts exploring a network-centric Extended Evolutionary Synthesis.

Michael Levin at Tufts explores bioelectric and morphogenetic fields that act as information-processing networks guiding development. He also has a uniquely multiscale, network-centric, devo-evo understanding of agency (see his Architecture of Agency 2026). The deep robustness in embryonic development (capacity to arrive at predictable future form even under mechanical disruption) is a network agency phenomenon. Levin treats organisms as cognitive agents at multiple scales, including fields, chemistry, cells, tissues, organs, and organisms, each with their own problem-solving capacities. His work on basal cognition, explored in papers like Mind Everywhere (2026) coauthored with David B. Resnik, treats cognition as a spectrum from minimal cellular agency to human consciousness. It is a promising union of developmental biology, information, computation, physics, and cognitive science. Along with scholars like Terrence Deacon (below), Levin's approach brings teleology (goal directedness) back into evolution and agency theory as teleonomy (entrained adaptive processes), emergent under selection.

Agency - Information, Computation, Neuro, Learning, and Intelligence

Simon De Deo at Carnegie Mellon/Santa Fe works on information theory, learning, and the emergence of predictability from unpredictable substrates in biological, cognitive, and social systems. His 2020 paper with Scott Viteri on epistemic phase transitions that occur in the emergence of human belief in the veracity of mathematical proofs expores how complex agentic systems build confidence in modelling their environment. De Deo's approach is deeply consilient with predictive processing models at all scales of biology, including genetic, cell signaling, and neural networks.

News

Visit and critique our latest topic pages:

• Evolutionary Cosmology
• Evolutionary Development
• Convergent Evolution and Universal Development.
• Self-Organization (coming next).

Win or contribute to the High Energy Astrobiology Prize. Does advanced life create a subset of binary stars (stellivore hypothesis)?.

Visit and comment at our EDU blog

Community Conferences

The annual Conference on Complex Systems of the Complex Systems Society is our current primary community where we convene and explore the systems theory and philosophy of evolution, development, and adaptiveness in autopoietic systems at all scales.

Websites of our most recent CCS satellite meetings:

Physics of Self-Organization at CCS 2025 in Siena, Italy.

Physics of Self-Organization at CCS 2024 in Exeter, United Kingdom.

Physics of Self-Organization at CCS 2023 in Salvador, Brazil.

Physics of Self-Organization at CCS 2020 (virtual conference during the COVID-19 pandemic)

Physics of Self-Organization at CCS 2018 in Thessaloniki, Greece.

Efficiency in Complex Systems at CCS 2017 in Cancun, Mexico.

Evolution, Development, and Complexity at CCS 2017 in Cancun, Mexico.

Thanks to all the scientists, researchers, complex systems scholars and philosophers who present at or attend these meetings. Without you, our field would not advance.

Our Latest Book

Our latest edited volume of EDU-related research Evolution, Development and Complexity, came out in the Springer Complexity Series in 2019. This book is a testament to the great and still-underappreciated value of what we call Biology-Inspired Complexity Science & Philosophy, the central theme of our EDU community. See the Satellite website for abstracts. To be considered for future publications, contact lead editor Georgi Georgiev with an abstract of your related work.

Select Member Publications

Clément Vidal's book: The Beginning and the End: The Meaning of Life in a Cosmological Perspective, 2014, Springer.

John O. Campbell's books: Darwin Does Physics, 2015 and The Knowing Universe, 2021. A largely unnoticed scientific revolution has occurred over the past forty-five years. The Darwinian paradigm has been successfully applied to numerous fields outside of biology: including the social and behavioral sciences and most recently to the physical sciences. Longstanding concepts in physics and information theory, including the free energy principle and Bayesian inference, are now being used to model how information becomes knowledge in a great variety of adaptive systems, including quantum, molecular, cellular, neural, cultural, and technological systems, and even to contemplate our universe itself as an autopoietic (evo-devo) learning system. Such autopoietic, model-centric, and selectionist approaches promise a conceptual unification of many branches of science.

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Academic Tributes

Read our tribute pages, honoring the work of our late EDU Community Scholars. Each of these scholars have made notable contributions to the understanding of our universe as a complex evolutionary and developmental learning system, with many autopoietic subsystems, all under various forms of adaptive selection. Tributes are alpha by last name.

The distinguished evolutionary systems theorist John Oberon Campbell (1949-2023), a pioneer in understanding the relationship of selection, information and learning to adaptiveness in the universe, life, and other complex systems, and a distinguished scholar in our EDU community.

The distinguished lawyer and complexity theorist James N. Gardner (1946-2021), author of the selfish biocosm hypothesis (Biocosm, 2003), an extension of cosmological natural selection proposing that universal life and intelligence are intrinsic to cosmic evolution and reproduction, and a presenter at our 2008 Paris conference.

The distinguished developmental and evolutionary systems theorist Stanley N. Salthe (1930-2024), a pioneer in the development-first view of life and our universe, and a founding scholar in our EDU community.

The distinguished biogeochemist David W. Schwartzman (1943-2025), a pioneer in characterizing biospheric self-regulation, the co-evolution of life and environment in the early Earth, and Earth as a developmental system for the coarsely deterministic emergence of life.

The distinguished nuclear physicist and systems theorist Peter Winiwarter (1945-2009), author, Neural Network Nature, 2010 and Founder, Bordalier Institute, Boursay, France, and an early member of our EDU community.

Mission

The mission of the EDU Research Community is to explore how our understanding of the universe as a complex system might be augmented by insights from information and computation studies, evolutionary developmental (evo-devo) biology, and hypotheses and models of quasi-evolutionary and quasi-developmental process applied at universal and subsystem scales. The major focus of our community is Biology-Inspired Complexity Science and Philosophy (BICS&P) in ten areas of universal complexity. We think this approach helps us address a few of the "missing links" in complexity research today.

The underlying paradigm for cosmology is theoretical physics. It has helped us understand much about universal space, time, energy, and matter, but does not presently connect strongly to the emergence of information, computation, life and mind.

In the neo-Darwinian paradigm, adaptive evolutionary development guides the production of ordered, complex and intelligent structures. When we consider informational algorithms in biological systems, we can distinguish evolutionary processes which are stochastic, variety-creating, divergent, and contingently adaptive and developmental processes which produce convergent and systemically statistically predictable structures and trajectories internal to the developmental cycle. Such evo and devo algorithms emerged via replication and various selection functions, depending on environment. By analogy with the evolutionary development of two genetically identical twins, a variety of cosmology models predict that two parametrically identical universes would each exhibit unpredictably separate and unique "evolutionary" variation over their lifespan, and at the same time, a broad set of predictable "developmental" shared structure, function, and emergence timelines between them. But how much of the advanced complexity we see around us is developmental? How can we explore this question of the extent of universal development, via astrobiology, simulation, and our models of context-specific and general adaptiveness?

In what other ways does our universe appear to be an evolutionary developmental system? What models suggest our universe may replicate and be selected upon in some extrauniversal environment? How do unpredictability and predictability interact in all replicating systems within our universe, from stars to chemistry to life, and what generic selection functions apply? To what extent may these intrauniversal models help us understand the way unpredictability and predictability work together in physics and cosmology, in service to universal complexity?

We are particularly interested in exploring hypotheses of universal evolutionary process (sometimes called "Universal Darwinism"), and universal developmental process (constraining and future-predictable laws, hierarchy, form, function, and life cycle) which may be operating in complex adaptive systems at all scales. We seek to better understand evolutionary and developmental processes of self-organization and adaptation at all scales, including the universal scale. If universe is a replicator within the multiverse, as preliminary models like cosmological natural selection propose, it would be expected to adaptively self-organize both its evolutionary and developmental processes, just as those processes have self-organized in living systems. Evo-devo models propose that not only is our universe in many ways evolutionary (creative, selectionist, contingent), but it is also developmental (conservative, hierarchical, convergent), as one would expect under replication with selection. For example, the isotropy, compartmentalization, parallelism, and far-future similarity (convergence) we find in universal complex structure and function, at the hierarchy levels of galaxies, stars, and rocky planets, and which may also include astrobiological life and intelligence, has many physical and informational parallels to the isotropy, compartmentalization, parallelism, and far-future similarity seen in biological development.

For more, please see the EDU Project page. A brief article on our work by Michael Chorost: Title: The Ascent of Life (PDF). New Scientist magazine, 21 Jan 2012, pp. 35-37.

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Listserves, People, Themes, Questions, Bibliography, and SIGs

For EDU notice and discussion lists, see Listserves. For current EDU community scholars and associates, please see the People page. For a list of research themes, see the Themes page. For some current research questions, see the Questions page. For a starter list of EDU-related publications by community scholars, and other publications of note, see Bibliography. For a list of primary special interest groups, see SIGs. For a list of future conference themes and proposals, see Conference Themes.

Founding Conference

Our first international EDU conference, Oct 8-9 2008 in Paris, France. It started our community, which has steadily grown since then on our listserves. See the Conference 2008 page for EDU 2008 program, abstracts, slides, and some audio of presentations.

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Invitation

Do you have a respectable scientific community to discuss your more heterodox (unorthodox, provocative, exploratory) ideas in evolution, development, and complexity? Maybe you have a model or theory, or wish to discuss, critique, or design an experiment to evaluate a model or theory, that is a bit outside the mainstream? Intellectual breakthroughs don’t always fit with established traditions. We take this fact seriously in the EDU community, and offer a forum for careful, evidence-seeking discussion and critique of more creative and daring hypotheses. Evo-Devo Universe has over a hundred academically-affiliated scholars from a wide variety of disciplines, engaged in serious, courteous, open-minded, constructive, and private discussion of the frontiers of science, in our main themes of evolution, development, and complexity. Our community uses the Chatham House Rule, where scholars are free to use the information from the discussion, but are not allowed to reveal the source, without that source's permission. This encourages high-reputation scholars to engage in frank debates on controversial topics, and to express early intuitions and tentative opinions that would not otherwise be expressed in more public venues.

Objectives (Mission)

1. To establish an evo-devo universe (EDU) research community to explore ideas, models, and questions involving evolutionary and developmental processes operating in the universe as a system, which may or may not exist within a more extensive cosmologic environment (the multiverse). This includes explorations of multi-scale intrauniversal autopoietic processes (universal selection theory), their homologies to the universe as a complex system, and the topic of universal phylogeny, the hypothesis that universe(s) were the original replicator(s), the LUCA for physical and informational reality, as is proposed in the hypothesis of cosmological natural selection.
   
2. To bring together select cosmologists, physicists, chemists, biologists, complexity theorists, mathematicians, systems theorists, information theorists, computer scientists, philosophers, independent scholars, and bridge-building interdisciplinarians who have all addressed dimensions of this inquiry in previous publications.
   
3. To identify a multidisciplinary global community of scholars with interest in exploring the science and philosophy of the universe, and its subsystems, as evolutionary and developmental systems, and the universe, and its subsystems, as complex adaptive system, in discriminating potential evolutionary and developmental processes and their interrelationships in any system, and in exploring the selective and network-centric processes that manage the tension between creative evolutionary and conservative developmental process, at all scales.
   
4. To conduct a periodic inquiry, conference publication series, and open access overview of current thinking on the evolution and development of the universe and its subsystems.
   

How can I participate?

There are several ways you can participate in the Evo-Devo Universe (EDU) community.

• Institutionally-affiliated academics and a limited number of independent scholars are encouraged to join the EDU-Talk discussion list, a moderated private list for scholars interested in exploring and critiquing models, hypotheses, questions, and speculations relating to the evolution and development of the universe and its subsystems. Your membership on the list can be public or private, as you prefer. Please complete the brief EDU-Talk subscription form.

• Consider coming to and presenting at one of our One-Day Conferences, typically co-located with other academic conferences, where you will meet and can build collaborations with other scholars with similar interests. You are also encouraged to start a SIG within our community on your particular subject of interest.

• If you are a researcher in physics, cosmology, chemistry, biology, philosophy, information, computation, complexity sciences or other field who is considering some of our Research questions, we will be glad to welcome you as a publicly listed member of the community, on our People page.

• If you are interested in doing bibliographic research, scholar recruiting, or community support, we will be glad to welcome you as an Associate member of the community. Perhaps you would like to help us build our bibliography and global scholar network related to EDU themes. We also welcome bibliographic and scholar recruitment suggestions.

• Anyone may join our public EDU-Notices list. This moderated, announcement-only list is low volume and will keep you abreast of EDU Community activities (conferences, publications, etc.). Members may also post notices of important events, call for papers, publications, etc. on EDU-related themes (notices subject to moderator approval) .

• We greatly appreciate one-time or ongoing financial support and any help or advice related to fundraising for the project. Individual or institutional donations may be made to the Evo-Devo Institute, the 501c3 nonprofit sponsoring this research community (est. 2008).

• We are grateful for initial funding of the project by The Complex Systems Institute, Paris (ISC-PIF)