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Global brain

Global brain
Related:  Network Science

The Global Brain Institute The GBI uses scientific methods to better understand the global evolution towards ever-stronger connectivity between people, software and machines. By developing concrete models of this development, we can anticipate both its promises and its perils. That would help us to steer a course towards the best possible outcome for humanity. Objectives (for more details, check our strategic objectives and activities) Assumptions We see people, machines and software systems as agents that communicate via a complex network of communication links. Challenges that cannot be fully resolved by a single agent are propagated to other agents, along the links in the network. The propagation of challenges across the global network is a complex process of self-organization.

Swarm intelligence Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems.[1] The application of swarm principles to robots is called swarm robotics, while 'swarm intelligence' refers to the more general set of algorithms. 'Swarm prediction' has been used in the context of forecasting problems. Example algorithms[edit] Particle swarm optimization[edit] Ant colony optimization[edit] Artificial bee colony algorithm[edit] Artificial bee colony algorithm (ABC) is a meta-heuristic algorithm introduced by Karaboga in 2005,[5] and simulates the foraging behaviour of honey bees. Bacterial colony optimization[edit] Differential evolution[edit] Differential evolution is similar to genetic algorithm and pattern search. The bees algorithm[edit] Artificial immune systems[edit] Bat algorithm[edit]

Holarchy Different meanings[edit] David Spangler uses the term in a different meaning: "In a hierarchy, participants can be compared and evaluated on the basis of position, rank, relative power, seniority, and the like. But in a holarchy each person’s value comes from his or her individuality and uniqueness and the capacity to engage and interact with others to make the fruits of that uniqueness available."[2] In multiagent systems[edit] Multiagent systems are systems composed of autonomous software entities. Janus Multiagent Platform is a software platform able to execute holarchies of agents. See also[edit] References[edit] External links[edit] Brief essay on holarchies

Gaia hypothesis Paradigm that living organisms interact with their surroundings in a self-regulating system The Gaia hypothesis (), also known as the Gaia theory, Gaia paradigm, or the Gaia principle, proposes that living organisms interact with their inorganic surroundings on Earth to form a synergistic and self-regulating, complex system that helps to maintain and perpetuate the conditions for life on the planet. The Gaia hypothesis was formulated by the chemist James Lovelock[1] and co-developed by the microbiologist Lynn Margulis in the 1970s.[2] Following the suggestion by his neighbour, novelist William Golding, Lovelock named the hypothesis after Gaia, the primordial deity who personified the Earth in Greek mythology. In 2006, the Geological Society of London awarded Lovelock the Wollaston Medal in part for his work on the Gaia hypothesis.[3] Overview[edit] The Gaia paradigm was an influence on the deep ecology movement.[12] Details[edit] Regulation of global surface temperature[edit] History[edit]

How to Burst the "Filter Bubble" that Protects Us from Opposing Views The term “filter bubble” entered the public domain back in 2011when the internet activist Eli Pariser coined it to refer to the way recommendation engines shield people from certain aspects of the real world. Pariser used the example of two people who googled the term “BP”. One received links to investment news about BP while the other received links to the Deepwater Horizon oil spill, presumably as a result of some recommendation algorithm. This is an insidious problem. This is the filter bubble—being surrounded only by people you like and content that you agree with. And the danger is that it can polarise populations creating potentially harmful divisions in society. Today, Eduardo Graells-Garrido at the Universitat Pompeu Fabra in Barcelona as well as Mounia Lalmas and Daniel Quercia, both at Yahoo Labs, say they’ve hit on a way to burst the filter bubble. They found over 40,000 Twitter users who had expressed an opinion using the hashtags such as #pro-life and #pro-choice.

Craig Reynolds (computer graphics) Craig W. Reynolds (born March 15, 1953), is an artificial life and computer graphics expert, who created the Boids artificial life simulation in 1986.[1] Reynolds worked on the film Tron (1982) as a scene programmer, and on Batman Returns (1992) as part of the video image crew. Reynolds won the 1998 Academy Scientific and Technical Award in recognition of "his pioneering contributions to the development of three-dimensional computer animation for motion picture production."[2] He is the author of the OpenSteer library.

Holism and Evolution 1926 book by Jan Smuts Holism and Evolution is a 1926 book by South African statesman Jan Smuts, in which he coined the word "holism",[1][2] although Smuts' meaning differs from the modern concept of holism.[3] Smuts defined holism as the "fundamental factor operative towards the creation of wholes in the universe."[4] The book was part of a broader trend of interest in holism in European and colonial academia during the early twentieth century.[1] Smuts based his philosophy of holism on the thoughts behind his earlier book, Walt Whitman: A Study in the Evolution of Personality, written during his time at Cambridge in the early 1890s.[5][6] The book describes a "process-orientated, hierarchical view of nature" and has been influential among criticisms of reductionism.[3] Smuts saw the League of Nations as a project that would unify white internationalists and pacify a forthcoming race war by establishing a mandate system, whereby whites would indirectly rule and segregate non-whites.[8]

Francis Heylighen Belgian cyberneticist (born 1960) Francis Paul Heylighen (born 27 September 1960) is a Belgian cyberneticist investigating the emergence and evolution of intelligent organization. He presently works as a research professor at the Vrije Universiteit Brussel (the Dutch-speaking Free University of Brussels), where he directs the transdisciplinary research group on "Evolution, Complexity and Cognition"[1][2] and the Global Brain Institute. He is best known for his work on the Principia Cybernetica Project, his model of the Internet as a global brain, and his contributions to the theories of memetics and self-organization. He is also known, albeit to a lesser extent, for his work on gifted people and their problems. Biography[edit] Francis Heylighen was born on September 27, 1960 in Vilvoorde, Belgium. In 1983 he started working as a researcher for the Belgian National Fund for Scientific Research (NFWO). Work[edit] Basic ideas[edit] Principia Cybernetica[edit] The Global Brain[edit]

US Military Scientists Solve the Fundamental Problem of Viral Marketing Viral messages begin life by infecting a few individuals and then start to spread across a network. The most infectious end up contaminating more or less everybody. Just how and why this happens is the subject of much study and debate. Network scientists know that key factors are the rate at which people become infected, the “connectedness” of the network and how the seed group of individuals, who first become infected, are linked to the rest. It is this seed group that fascinates everybody from marketers wanting to sell Viagra to epidemiologists wanting to study the spread of HIV. So a way of finding seed groups in a given social network would surely be a useful trick, not to mention a valuable one. These guys have found a way to identify a seed group that, when infected, can spread a message across an entire network. Their method is relatively straightforward. This process finishes when there is nobody left in the network who has more friends than the threshold. Expect to hear more!

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