The new science of complex systems will be at the heart of the future of the Worldwide Knowledge Society. It is providing radical new ways of understanding the physical, biological, ecological, and techno-social universe. Complex Systems are open, value-laden, multi-level, multi-component, reconfigurable systems of systems, situated in turbulent, unstable, and changing environments. They evolve, adapt and transform through internal and external dynamic interactions. They are the source of very difficult scientific challenges for observing, understanding, reconstructing and predicting their multi-scale dynamics. The challenges posed by the multi-scale modelling of both natural and artificial adaptive complex systems can only be met with radically new collective strategies for research and teaching (...)
Cooperation is one of the essential factors for all biological organisms in major evolutionary transitions. Recent studies have investigated the effect of migration for the evolution of cooperation. However, little is known about whether and how an individuals’ cooperativeness coevolves with mobility. One possibility is that mobility enhances cooperation by enabling cooperators to escape from defectors and form clusters; the other possibility is that mobility inhibits cooperation by helping the defectors to catch and exploit the groups of cooperators. In this study we investigate the coevolutionary dynamics by using the prisoner’s dilemma game model on a lattice structure. The computer simulations demonstrate that natural selection maintains cooperation in the form of evolutionary chasing between the cooperators and defectors. First, cooperative groups grow and collectively move in the same direction. Then, mutant defectors emerge and invade the cooperative groups, after which the defectors exploit the cooperators. Then other cooperative groups emerge due to mutation and the cycle is repeated. Here, it is worth noting that, as a result of natural selection, the mobility evolves towards directional migration, but not to random or completely fixed migration. Furthermore, with directional migration, the rate of global population extinction is lower when compared with other cases without the evolution of mobility (i.e., when mobility is preset to random or fixed). These findings illustrate the coevolutionary dynamics of cooperation and mobility through the directional chasing between cooperators and defectors.
John Tyler Bonner, one of our most distinguished and insightful biologists, here challenges a central tenet of evolutionary biology. In this concise, elegantly written book, he makes the bold and provocative claim that some biological diversity may be explained by something other than natural selection.
With his customary wit and accessible style, Bonner makes an argument for the underappreciated role that randomness--or chance--plays in evolution. Due to the tremendous and enduring influence of Darwin's natural selection, the importance of randomness has been to some extent overshadowed. Bonner shows how the effects of randomness differ for organisms of different sizes, and how the smaller an organism is, the more likely it is that morphological differences will be random and selection may not be involved to any degree. He traces the increase in size and complexity of organisms over geological time, and looks at the varying significance of randomness at different size levels, from microorganisms to large mammals. Bonner also discusses how sexual cycles vary depending on size and complexity, and how the trend away from randomness in higher forms has even been reversed in some social organisms.
Research has progressed through three ages: the individual, the institutional and the national. Nations competed to be at the cutting edge because this contributed to the wider economy through knowledge, new processes and products.
Today, we are entering a fourth age of research, driven by international collaborations between elite research groups. This will challenge the ability of nations to conserve their scientific wealth either as intellectual property or as research talent. Tensions are growing: between the knowledge a country needs to remain competitive and the assets it can exclusively secure, and between the collaborative and domestic parts of the research base. Institutions that do not form international collaborations risk progressive disenfranchisement, and countries that do not nurture their talent will lose out entirely.
Plants represent almost 99.9% of the biomass of our planet. This means that virtually every environment that can be colonized by life has been explored and populated by plants. To achieve such amazing results while being unable to move from the site of seed germination, plants have evolved an arsenal of solutions that make them suitable for life in the most demanding and extreme conditions. In addition, it is well established that plants are able to show considerable plasticity in their morphology and physiology in response to variability within their environment and to survive extremely diverse environmental conditions and stresses (Fujita et al (2006)). Thus the mechanical properties of plants, the morphology of their structures and their characteristic movements represent a goldmine of solutions that, with appropriate investigation, could be used to obtain new design rules for advanced bioinspired systems and materials in countless applications. Meanwhile, advances in technology, partly related to the adoption of such bio-inspired approaches in design, are opening new opportunities for the application of bioinspired artefacts in biological research.
The cosmological natural selection (CNS) hypothesis holds that the fundamental constants of nature have been fine-tuned by an evolutionary process in which universes produce daughter universes via the formation of black holes. Here, we formulate the CNS hypothesis using standard mathematical tools of evolutionary biology. Specifically, we capture the dynamics of CNS using Price's equation, and we capture the adaptive purpose of the universe using an optimization program. We establish mathematical correspondences between the dynamics and optimization formalisms, confirming that CNS acts according to a formal design objective, with successive generations of universes appearing designed to produce black holes.
Cosmological natural selection and the purpose of the universe
As machines take on more jobs, many find themselves out of work or with raises indefinitely postponed. Is this the end of growth? No, says Erik Brynjolfsson -- it’s simply the growing pains of a radically reorganized economy. A riveting case for why big innovations are ahead of us … if we think of computers as our teammates. Be sure to watch the opposing viewpoint from Robert Gordon.
(Phys.org)—Multicellularity in cyanobacteria originated before 2.4 billion years ago and is associated with the accumulation of atmospheric oxygen, subsequently enabling the evolution of aerobic life, as we know it today.
This crazy looking thing is a simulated robot, made up of two different kinds of muscles along with bones and soft tissue for structure. This robot wasn't designed, it was evolved over a thousand virtual generations to move as fast, as far, and as functionally as possible.
More than one billion people lack access to clean drinking water, sufficient food and electricity. Meanwhile, the global population is growing by some 80 million people every year. By 2030, the nine billion people living on earth will need 30% more water, 40% more energy and 50% more food to survive. Given the complex relationships among all three resources -- the nexus of food, energy and water -- meeting these demands will require thinking in terms of systems, not silos. It will take collaborative approaches that embrace rather than battle natural processes. And it will mean new technologies and approaches to everything from bio-fuels to desalination. This special report, produced in coordination with Wharton's Initiative for Global Environmental Leadership (IGEL), takes a close look at the key issues.
A phyllosilicate is a sheet of silicate tetrahedra bound by basal oxygens. A phyllosilicate automaton is a regular network of finite state machines --- silicon nodes and oxygen nodes --- which mimics structure of the phyllosilicate. A node takes states 0 and 1. Each node updates its state in discrete time depending on a sum of states of its three (silicon) or six (oxygen) neighbours. Phyllosilicate automata exhibit localizations attributed to Conway's Game of Life: gliders, oscillators, still lifes, and a glider gun. Configurations and behaviour of typical localizations, and interactions between the localizations are illustrated.
Game of Life on Phyllosilicates: Gliders, Oscillators and Still Life
State-of-the-art DNA sequencing is providing ever more detailed insights into the genomes of humans, extant apes, and even extinct hominins, offering unprecedented opportunities to uncover the molecular variants that make us human. A common assumption is that the emergence of behaviorally modern humans after 200,000 years ago required—and followed—a specific biological change triggered by one or more genetic mutations. For example, Klein has argued that the dawn of human culture stemmed from a single genetic change that “fostered the uniquely modern ability to adapt to a remarkable range of natural and social circumstance”. But are evolutionary changes in our genome a cause or a consequence of cultural innovation?
Culture, Genes, and the Human Revolution Simon E. Fisher, Matt Ridley
Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to adaptive success. This target article critically examines this “hierarchical prediction machine” approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action.
Whatever next? Predictive brains, situated agents, and the future of cognitive science Andy Clark
Behavioral and Brain Sciences / Volume 36 / Issue 03 / June 2013, pp 181-204
"Cartesian-inspired dualism enforces a theoretical distinction between the motor and the cognitive and locates the mental exclusively in the head. This collection, focusing on the hand, challenges this dichotomy, offering theoretical and empirical perspectives on the interconnectedness and interdependence of the manual and mental. The contributors explore the possibility that the hand, far from being the merely mechanical executor of preconceived mental plans, possesses its own know-how, enabling “enhanded” beings to navigate the natural, social, and cultural world without engaging propositional thought, consciousness, and deliberation.
The contributors consider not only broad philosophical questions—ranging from the nature of embodiment, enaction, and the extended mind to the phenomenology of agency—but also such specific issues as touching, grasping, gesturing, sociality, and simulation. They show that the capacities of the hand include perception (on its own and in association with other modalities), action, (extended) cognition, social interaction, and communication. Taken together, their accounts offer a handbook of cutting-edge research exploring the ways that the manual shapes and reshapes the mental and creates conditions for embodied agents to act in the world".
A single equation grounded in basic physics principles could describe intelligence and stimulate new insights in fields as diverse as finance and robotics, according to new research.
Alexander Wissner-Gross, a physicist at Harvard University and the Massachusetts Institute of Technology, and Cameron Freer, a mathematician at the University of Hawaii at Manoa, developed an equation that they say describes many intelligent or cognitive behaviors, such as upright walking and tool use.
The researchers suggest that intelligent behavior stems from the impulse to seize control of future events in the environment. This is the exact opposite of the classic science-fiction scenario in which computers or robots become intelligent, then set their sights on taking over the world.
The findings describe a mathematical relationship that can "spontaneously induce remarkably sophisticated behaviors associated with the human 'cognitive niche,' including tool use and social cooperation, in simple physical systems," the researchers wrote in a paper published today in the journal Physical Review Letters.
"It's a provocative paper," said Simon DeDeo, a research fellow at the Santa Fe Institute, who studies biological and social systems. "It's not science as usual."
Wissner-Gross, a physicist, said the research was "very ambitious" and cited developments in multiple fields as the major inspirations.
The mathematics behind the research comes from the theory of how heat energy can do work and diffuse over time, called thermodynamics. One of the core concepts in physics is called entropy, which refers to the tendency of systems to evolve toward larger amounts of disorder. The second law of thermodynamics explains how in any isolated system, the amount of entropy tends to increase. A mirror can shatter into many pieces, but a collection of broken pieces will not reassemble into a mirror.
The new research proposes that entropy is directly connected to intelligent behavior.
Drew Endy wants to build a programming language for the body.
Endy is the co-director of the International Open Facility Advancing Biotechnology — BIOFAB, for short — where he’s part of a team that’s developing a language that will use genetic data to actually program biological cells. That may seem like the stuff of science fiction, but the project is already underway, and the team intends to open source the language, so that other scientists can use it and modify it and perfect it.
The effort is part of a sweeping movement to grab hold of our genetic data and directly improve the way our bodies behave — a process known as bioengineering. With the Supreme Court exploring whether genes can be patented, the bioengineering world is at crossroads, but scientists like Endy continue to push this technology forward.
Genes contain information that defines the way our cells function, and some parts of the genome express themselves in much the same way across different types of cells and organisms. This would allow Endy and his team to build a language scientists could use to carefully engineer gene expression – what they call “the layer between the genome and all the dynamic processes of life.”
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