Evolutionary cosmology

Evolutionary Cosmology ("EvoCosmo") is a new and fast-growing scientific field that takes ideas from evolutionary, developmental, and theoretical biology, plus systems theory and information theory, and applies them to cosmology, astronomy and astrophysics. (Those ideas and their application are described in more detail below.) In this, it shares much with the relatively young concept of Universal Darwinism, which explores Darwinian selectionist and self-organizing processes at all scales, from physics and chemistry to biology and culture: but in this case, applied to the universe itself as the unit of selection.

Cosmological Natural Selection (CNS)

At the core of Evolutionary Cosmology is an exploration of the idea that our universe is the result of a modified Darwinian evolutionary process. As such it builds upon Cosmological natural selection (CNS), the fecund universes theory, first proposed by the American theoretical physicist Lee Smolin in the 1990s, most famously in his initial paper "Did the universe evolve?” (1992), and book The Life of the Cosmos (1997), and over more than two decades of periodic followup work. In physics, CNS is a subfield of black hole cosmology, the set of theories that propose our universe is both the interior and outgrowth of a black hole. It suggests a seed-organism-environment complexity partitioning dynamic, in which black holes function as an initiating seed, organisms the cycling universe, and the multiverse a potential or actual environment. CNS has been misinterpreted by some theorists as predicting "maximal" black hole and universe production, when in reality, it is a fecund universes theory, in which neither black hole or universe production is maximal, but rather adaptively fecund, and perhaps constrained by a resource or computational tradeoff between black hole production and organism (universe) complexity (see The Smolin-Susskind Debate). Besides Smolin, there has been further development of CNS ideas since the 1990s by scholars from a wide range of disciplines including Quentin Smith (1990), Stephen Hawking (1993), Louis Crane (1994, 2010), Edward Harrison (1995), John M. Smart (2000, 2003, 2005, 2009, 2012, 2019), Vladimir Lefebvre and Yuri Efremov (2000); James N. Gardner (2000, 2003, 2007), Clément Vidal (2010, 2011, 2012, 2013, 2016, 2019, 2024), Vidal et al. (2026), Rüdiger Vaas (2009), John O. Campbell (2011, 2015, 2019), Andy Gardner and Joseph P. Conlon (2013), Michael E. Price (2019), Jeffrey M. Shainline (2020), Stephon Alexander (2021), Julian Gough (2022, 2025, 2026) and Bobby Azarian (2022).

Often independently, they have explored an evolutionary explanation for the anthropic principle (Carroll 2004), in which associative (network-centric) evolutionary and developmental intelligence may naturally emerge with increasing diversity, predictability, and complexity over replication histories, if that intelligence serves some nonrandom selection function. Since the 19th century, life's intelligence has been narrowly claimed to alter selection pressures on heritable traits as units of selection (Darwin 1859, Lewes 1873, Baldwin 1896, Simpson 1953). Some theorists have also made a broader claim: intelligence, with its superior search and modeling functions, may incrementally enhance the reproductive success of a special subset of organisms and their dependent subsystems (Spencer 1855, Wallace 1864, Darwin 1871; Miller 1978, 1995). This broader claim was made, in outline, by Darwin himself in The Decent of Man (1871). If our cosmos itself is a replicator, subject to some selection function (self-organization for life-cycle stability, resource efficiency or modeling complexity, cooperation or competition with other replicators, or some other function), and if emergent intelligence can nonrandomly affect the initial or boundary conditions of successor universes at the replication point, the same intelligence-emergence dynamics may be expected to occur. Under such assumptions, we may reasonably expect to live in a cosmos that has been iteratively tuned for both a useful diversity of evolutionary intelligence experiments within its life cycle, and for efficient and robust hierarchical development across its life cycle. At first glance, we appear to exist in a universe capable of massively parallel contingent local complexity experiments, and one with multi-scale, macrotemporal developmental dynamics. Though we have scant theory for it today, some mechanism for intelligence comparison by advanced intelligences prior to replication may also be expected to emerge over successive iterations, if the laws of physics and informatics allow it.

This extension of CNS is has been called many names by these authors, including Cosmological Natural Selection with Intelligence (CNS-I), Cosmological Artificial Selection (CAS), Cosmic Convergent Evolution (CCE), Cosmic Intelligence (CI), Cosmological Intelligence Selection (CIS), the Autodidactic Universe (AU), Cosmological Learning (CL) and CNS 2.0. The terms CNS and CL are most commonly used by the Evo-Devo Universe community. In coming years, we hope that the best-known of these terms CNS remains the main term of use, but becomes increasingly understood to be a model in which the initiating parameters may assort near-randomly at the beginning of universal phylogeny, as Smolin initially proposed in CNS, but can do so increasingly nonrandomly as intelligence accretively develops in some "later" and "higher" universe lineages, just as Darwin himself argued for the human lineage adapting in nature. Included in these new CNS models is the assumption that end-of-universe intelligences are not omniscient or omnipotent, and perhaps not even able to vary the all of the parameters of the subsequent universe without developmental disruption. Instead, they are assumed to be computationally finite systems, with limited forward knowledge and action capacity, perennially facing a combinatorial explosion of possible future states and actions. A common assumption, in other words, is that physical intelligences of any kind can never fully optimize their future universal states, but must satisfice (Simon 1955, 1956) on adaptive landscapes, and thus must remain constrained to making intelligence-guided guesses, under selection.

Included under the Cosmological Learning umbrella are a range of more and less consensus ideas as the Cosmological Fine-Tuning Problem (aka Strong Anthropic Principle, aka Fitness of Earth-like Planets for Life) (Henderson 1913, Barrow & Tipler 1983, Sagan 1973, Barrow 2008), Least Action (Developmental Complexity Acceleration) in Self-Organization (Fuller 1938, Georgiev 2019;2025), Energetic Dissipation in Self-Organization (Prigogine 1978, Jantsch 1980, Chaisson 2001, England 2013, 2015), Convergent Evolution and Universal Development (Teilhard de Chardin 1959, Conway Morris 2003, McGhee 2011, 2019, Kirshenbaum 2020), the Meduso-Anthropic Principle (Crane 1994), the Selfish Biocosm Hypothesis (Gardner 2000), the Transcension Hypothesis (Smart 2005, 2012), Cosmological Artificial Selection (Vidal 2011), Universal Darwinism as Bayesian Inference (Campbell 2011, 2015), the Predictive Processing (Active Inference) Model of Mind (Friston 2010, Parr et.al. 2022), Niche Construction theory and 4E Cognition (Clark 2010, 2023, Odling-Smee 2013, Levin 2019), Cosmological Selection for Technology (Shainline 2020), the Autodidactic Universe (Alexander 2021), Machine Learning Over the String Theory Landscape (Halverson 2019, He 2022, Deen 2022), and even autodidactic (self-teaching, self-organizing) variants of the Simulation Hypothesis (Bostrom 2003).

Gardner's Biocosm (2003) and The Intelligent Universe (2007) offered the first book-length accounts of our universe as a CNS replicator aided by intelligence. Gardner speculated that our existing universe was deeply designed by prior end-of-universe "cosmic engineers". Alternatively, Smart's book Exploring the Technological Singularity (2003) and chapter, "Evo Devo Universe?" (2009) and Vidal's book and PhD thesis The Beginning and the End (2014) each proposed a CNS universe unlikely to have been either created ab initio or intelligently designed by Godlike beings, but rather "experimented with" by finite beings with limited foresight, simulation capacity, and power, beings that might remain constrained by many of inherited laws of cosmology that created them, and by natural laws operating for all universes with our dimensionality and type. Such a self-organizing universe (Jantsch 1980) may have only been nudged (artificially selected) in limited ways by ancestor intelligence. The limits of current and future intelligence in cosmological learning models are one of many topics for future research.

At present, Evolutionary Cosmology scholars are actively exploring the Three-Stage Cosmological Natural Selection (3CNS) model developed by Julian Gough in the early 2020s. This model proposes a developmental hierarchy of black-hole-directed universe formation, and proposes supermassive black holes as having a third, unique formation mechanism (direct collapse), likely to have been the first emergent mechanism in universal evolutionary development. This new approach generated a number of new predictions (Gough 2022). The subsequent confirmation of these predictions for supermassive black hole formation by the James Webb Space Telescope in July 2023 reinvigorated interest in CNS. Also being explored are the Blowtorch Theory (Gough 2025) of structure formation in the early universe, and the Compressed-Spring Model of galaxy formation (Gough 2026). Each is an extension of the 3CNS model, and each makes new predictions about large scale structure and galactic development.

The Problem that Evolutionary Cosmology Solves

The development of Cosmological Natural Selection models with a role for self-organizing intelligence has been greatly hampered by the lack of an existing and nonprejudiced scientific field in which to explore them. As has been noted, those working on the theory and its implications come from a wide variety of fields, including theoretical physics and cosmology (Smolin, Alexander), philosophy of science and astrobiology (Vidal), mathematics (Crane), evolutionary biology and "evo-devo" models (Price, Gardner, Conlon), developmental biology and "devo-evo" models (Hall, Wagner), living systems theory (Smart), English literature and philosophy (Gough), and astronomy (Harrison). It is also an area of study where publication has been quite disconnected and thus diluted in impact.

Without a formal field devoted to evolutionary cosmology theory, there has been no journal, formal or even informal, to consolidate publication and to disseminate relevant literature to interested scientists. Crucially, cosmologists have (perfectly understandably) no training in evolutionary, developmental, or systems biology, and most biologists have never even heard of the theory. The two key fields are completely isolated from each other at the institutional level. As a result, exploration and development of Cosmological Natural Selection has been incoherent, intermittent, and piecemeal since 1990, usually carried out by individual scientists in their spare time, with little to no institutional support or understanding.

Evolutionary Cosmology addresses this long-standing and mutually reinforcing set of problems in two ways: first, by defining and naming this previously vague and nameless field of inquiry, increasing its ability to be discussed and critically reviewed, and second, by inviting scholars and funders to join us to expore and support it at the Evo-Devo Institute. Please consider joining our listserve, publishing, finding collaborators, and copublishing with us as a named affiliation, and presenting or attending at our conferences, on a path to deeper collaboration and knowledge. Working together, we can share previously siloed knowledge, and inspire a new generation of scholars to explore, develop, and validate hypotheses and models within this vital new field, which has many potential implications for the strategies and purposes of life, intelligence, and humanity. Most auspiciously, modern AI research tools are making it easier than ever for scholars working on various aspects of evolutionary cosmology to "find their tribe", critique each other, and copublish.

On Scientific Prejudice Against Theories of Universal Development

A prejudice against theories of progressive development in nature has existed for over a century in science, for a complex set of historical and sociological reasons. Read Michael Ruse, From Monad to Man: The Concept of Progress in Evolutionary Biology, 2009, for a good account of this prejudice, which progressively emerged (irony intended) beginning in the early 20th century. During the 19th century, there were many respected philosophical treatises and models of predictable directional progress occuring in a subset of natural systems over macroevolutionary history. The most common name given to the general class of such theories was orthogenesis.

One early orthogenetic thesis is found in the work of Herbert Spencer. Spencer applied evolutionary theory to a wide variety of human cultural domains including science, politics, business, religion, and art. He proposed that there is a poorly characterized yet law-governed process of increasing developmental differentiation and complexity, acting most strongly on a subset of forms in every environment. He also emphasized personal and organizational liberty as crucial enablers of evolutionary development in human culture (Spencer 1857, 1890). Unlike some other orthogenetic thinkers (Lamarck 1809, Eimer 1898) who proposed some "vital" internal force drove complexification, and some who were religiously motivated, Spencer argued that the external competitive environment was a key influence on the selection for complex adaptations. Darwin himself was a progressionist in a tentative way, famously arguing that humans were a "higher form" than barnacles. One of the boldest [and still unresolved] theories of orthogenetic dynamics came from the naturalist Edward Drinker Cope, whose Law of Acceleration of Growth proposed [in our evo-devo language] that the most adaptive living systems engage in a predictable and progressive information compression of their early (prior) stages of development, over macroevolutionary history, in order to increasingly rapidly and efficiently reach an "evolutionary frontier" of experimentation and competitive adaptation (Cope 1868; Barnes 2024). His model remains perhaps the most intuitive way to understand the rapidly compressed changes developmental form seen in the early human embryo, a concept Ernst Haeckle independently popularized two years earlier as "ontogeny recapitulates phylogeny" (Haeckel 1866).

As evolutionary scholars, including Cope, increasingly abandoned religious explanations for orthogenesis in the late 19th century, orthogenetic theories themselves were increasingly attacked by leading evolutionary scholars. A consensus was reached in the mid 20th century, led by Ernst Mayr (1942) and Julian Huxley (1942) that such theories were outdated, supernatural, religiously influenced, or naively anthropocentric. Nuance was lost in considering such theories and it became unfashionable to even discuss them. Influential evolutionary scholars like George Gaylord Simpson when arguing against Eimer's definition of orthogenesis as a "straight line" evolution of forms, did not discuss the alternative hypothesis, entertained by Spencer and others, that directional progress might be saltationist ratchet emerging in a special subset of increasingly functionally complex environments. That latter argument was arguably also the view Wilhelm Haake, who coined the "orthogenesis" term in 1893, even though he, like Cope, was at the beginning also religiously influenced. By the 1950s, a strong consensus had formed in leading evolutionary research communities that such theories were both unscientific and often consciously or unconsciously religious in motivation. Funding and awards for the study of evolutionary progress dried up, and those who conducted it openly were subject to professional prejudice. Even adjacent concepts like convergent evolution were studied by only a handful of courageous scholars, given the implication that a subset of repetitive evolutionary convergences could then be candidates for a ratcheting process of directional, irreversible, progressive universal development.

Even today, Wikipedia incorrectly and prejudiciously calls orthogenesis an "obsolete biological hypothesis". Their editor's page on the topic focuses on the older, poorly-evidenced and vitalist "innate internal tendency" theories of progression, entirely ignoring decades of recent theories, often emerging by other names, that propose a ratcheting, accelerating progression of internal regulatory complexity and external cooperative and competitive complexity, general intelligence, and niche construction in a special subset of life's autopoietic systems. Any attempt to update Wikipedia pages on evolution or CNS to explain modern orthogenetic hypotheses is rejected by lead editors. We at EDI had to clone Wikipedia's deceptively incomplete page on Cosmological Natural Selection onto or own wiki (see our EDI page on Cosmological Natural Selection for comparison), in order to give it a proper treatment, after all our Wikipedia edits were removed by champions of the "modern" view that humanity inhabits a random, directionless universe, and the accompanying belief that any discussion otherwise must be religiously motivated.

Fortunately, a growing minority of evolutionarly scholars now see selectionist forces driving a subset of ecosystem actors toward progressive complexification, integration, and capacity for action in order to adapt. In the most complex or contested niches, various scholars have found macroevolutionary trends toward increased capacity for defensive and offensive power deployment, increased individual and collective simulation capacity (self, other, and world models, opportunity and threat modeling, inferential and deductive reasoning and strategic thinking), predictive processing capacity, and other forms of computational function or capacity growth. For a well-respected body of research on progressive directional trends in collective and individual power capacity in a subset of species, see Geerat Vermeij's Escalation Hypothesis (Vermeij 1987, 2023). For examples of what we could call a Computational Escalation Hypothesis progressively developing in a special subset of metazoans, in primates, and in human collective culture, see papers by Jolly 1966; Humphrey 1976; Maynard Smith & Szathmary 1995; Dunbar 1998; Godfrey-Smith 2002; Robson 2005; Jabonka & Lamb 2006; Ginsberg & Jablonka 2010; Friston 2010; Clark 2013; and Stewart 2014, for just a sample of good literature on the topic.

Such work need far greater funding and support, and we are not out of the woods yet. The contingent, environmentally-driven view of evolutionary innovation remains dominant in the Modern Evolutionary Synthesis, even as a minority of scholars (Noble 2011, Wagner 2014, Shapiro 2022) have documented many processes of internally-driven evolutionary innovation in response to sensed environmental change. Fortunately, advocates of an Extended Evolutionary Synthesis now incorporate concepts like structuralism (accretive developmental constraints) and evo-devo genetics as elements of an evolving model of life's complexification, moving the field of evolutionary biology slightly closer to engaging with the concepts of universal biology, hierarchy theory, and universal evolutionary development.

A Process Cosmology

To summarize, a key insight of evolutionary cosmology is that our universe behaves "much more like an egg than a rock", with the energy that moves through the system organising it into hierarchical (developmentally higher) levels of structured, orderly complexity over time, like an egg, rather than disordering it over time, like a rock. Evolutionary Cosmology posits that this is because a Darwinian evolutionary process at the level of universes has fine-tuned the basic parameters and initial conditions of physical and informational dynamics, and the relationships between them, so as to generate a highly reproductively successful universe, with three successive stages of black-hole coordinated reproduction, each of which evolved at a different point in the phylogenetic history of universes, and each of which is therefore more complex than the last.

Just as in biology, ontogeny (emergence) does not fully recapitulate phylogeny (evolutionary history), but it does deeply rhyme with it, and occasionally adds to it (Hall 2011). Elements of each stage in our universe’s developmental history have been conserved in some of their essentials, just as in biological development, because each is needed to build on, and emerges from, the previous one. What we therefore see in our universe, since the Big Bang, is a complex, structured, multi-stage developmental process of self-complexification and self-organization, with good evidence of previous phylogeny, if we know where and how to look.

Evolutionary cosmology is thus a “process cosmology” (Davis, Teixeira, and Schwartz 2022), analogous to the process biology of Denis Noble, Stuart Kauffman, Peter Corning, and others (Corning et al. 2023). It is also a “systems cosmology,” modeling our universe as a system of complex adaptive subsystems, with each subsystem supported by networks and embedded in a selective environment. In models like relational physics (Rovelli 2021) and dual-aspect monism (Atmanspacher & Rickles 2022), both informational and physical process, and the dynamic observer and the observed, have been analyzed as partially decomposable yet simulaneously unitary lenses on the same fundamental reality. Quantum information theorists, network information theorists, and others explore physical systems as computational, adaptive entities, with both unpredictable and predictable dynamics. Most centrally, it is an “autopoietic cosmology.” The word autopoiesis incorporates two fundamental features of certain complex systems. They engage in a conserved and predictable life cycle (auto--developmentally self-maintaining and self-replicating as senescence/entropy degrades their competitiveness) and they simultaneously engage in a variational, exploratory, and long-range unpredictable set of behaviors (poiesis--evolutionarily creative). We can observe autopoetic, network-centric "devo-evo" processes in systems at all scales in our universe, most canonically in living systems (Hall 2000; Wagner 2001). Yet dissipative systems such as spiral galaxies also repair and maintain themselves over time. Systems such as stars die and are replaced by new stars, outcompeting the local use of "star stuff" by non-autopoietic systems. Gases circulate, when they are near or within autopoietic systems, to where they may be used most efficiently, under gravitational least-action dynamics. Under Evolutionary Cosmology, not just galaxies but the universe as a whole can be considered, under hierarchy theory, as a nested set of locally adaptive and predictably emergent autopoietic systems.

Working Group

Julian Gough is the Director of the Evolutionary Cosmology Working Group at the Evo-Devo Institute. We are seeking cosmologists, physicists, chemists, evolutionary and developmental biologists, complexity and systems theorists, computer scientists, philosophers, science communicators, and others with an interest in advancing this research. We also welcome philanthropic funding. If you'd like to join our working group listserve, or have questions about our group, please contact Julian.

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