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Complexity Digest - Networking the Complexity Community

Complexity Digest - Networking the Complexity Community
Related:  scienceComplex Systems

Nature Publishing Group : science journals, jobs, and information Why we hate Complexity Natural and social systems are complex — that is, not entirely knowable, unpredictable, resistant to cause-and-effect analysis, in a word, mysterious. For our first three million years on Earth we humans, like every other species on the planet, accepted that mystery. We adapted rather than trying to change our environment. We evolved by learning to accommodate ourselves to our environment. Those unable to accommodate perished. But with the invention of civilization, we stopped accommodating change and started imposing it on our environment so we wouldn’t have to change. The problem is, our brains are severely limited in what they are capable of understanding. Once we invented civilization, and started to need to change our environment a lot, we needed to invent science. Even scientists loathe the imperfections in their models. One of the principles that stresses scientists, mathematicians, philosophers and theologists the most is the concept of infinity. Why?

Global Dynamics Processes: the Pattern which Connects from KaliYuga to Tao COMPLEX ADAPTIVE SYSTEMS GROUP AT IOWA STATE UNIVERSITY This page is maintained by the Artificial Intelligence Research Group in the Department of Computer Science at Iowa State University. Please mail additions and updates to this page to Vasant Honavar honavar@cs.iastate.edu. Many natural systems (e.g., brains, immune systems, ecologies, societies) and increasingly, many artificial systems (parallel and distributed computing systems, artificial intelligence systems, artificial neural networks, evolutionary programs) are characterized by apparently complex behaviors that emerge as a result of often nonlinear spatio-temporal interactions among a large number of component systems at different levels of organization. Complex Adaptive Systems Steering Committee At Iowa State University Participating Academic Departments This page is maintained by: Dr.

Kanzi Kanzi (born October 28, 1980), also known by the lexigram (from the character 太), is a male bonobo who has been featured in several studies on great ape language. According to Sue Savage-Rumbaugh, a primatologist who has studied the bonobo throughout her life, Kanzi has exhibited advanced linguistic aptitude.[1][2][3] Biography[edit] Born to Lorel and Bosandjo at Yerkes field station at Emory University and moved to the Language Research Center at Georgia State University, Kanzi was stolen and adopted shortly after birth by a more dominant female, Matata. Teco, son of Kanzi, was born June 1, 2010.[7] Teco has been exhibiting behaviors that resemble autism in young children.[8] Examples of Kanzi's behavior[edit] The following are highly suggestive anecdotes, not experimental demonstrations. Language[edit] See also[edit] References[edit] Further reading[edit] Joseph, John E., Nigel Love & Talbot J. External links[edit]

Complex systems made simple Albert-László Barabási and Yang-Yu Liu, together with their collaborator Jean-Jacques Slotine at M.I.T., have developed a method for observing large, complex systems. In the image above, red dots represent sensor nodes, which are required to reconstruct the entire internal state of one such system. Image by Mauro Martino. Just as the name implies, com­plex sys­tems are dif­fi­cult to tease apart. But that may not matter any­more. The approach takes advan­tage of the inter­de­pen­dent nature of com­plexity to devise a method for observing sys­tems that are oth­er­wise beyond quan­ti­ta­tive scrutiny. “Con­nect­ed­ness is the essence of com­plex sys­tems,” said Albert-​​László Barabási, one of the paper’s authors and a Dis­tin­guished Pro­fessor of Physics with joint appoint­ments in biology and the Col­lege of Com­puter and Infor­ma­tion Sci­ence. Using their novel approach, the researchers first iden­tify all the math­e­mat­ical equa­tions that describe the system’s dynamics.

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.

Complex Adaptive Systems Group Homepage Australia's Telerobot On The Web IF you are enrolled in Mechatronics and Multibody Systems 319, please refer to this instruction sheet. Otherwise, if you are a visitor....... Follow these instructions to start using the telerobot: Step 1: Install the software from the Download page Step 2: Run the "lol login" application (a shortcut should have been provided on your desktop). Step 3: Log in with your UserID and password. Step 4: In the student hallway, select the telerobot task. Help on using the Telelabs system is available here. Step 6: Once you have entered the lab, you will be presented with a screen similar to this: Making a Move: Select your desired X, Y, Z, Spin, Tilt, Gripper values. Detailed explanations of the interface follow: Camera Panel: Provides visual feedback for the Telerobot's table-top, as well as providing controls for the X, Y, Z values. Select Camera/Zoom Panel: Contains two drop-down menus that allow you to select the camera (and quality) you wish to view with, as well as a level of zoom.

Observability of complex systems Author Affiliations Edited by Giorgio Parisi, University of Rome, Rome, Italy, and approved December 26, 2012 (received for review September 6, 2012) Abstract A quantitative description of a complex system is inherently limited by our ability to estimate the system’s internal state from experimentally accessible outputs. Footnotes Author contributions: Y. VHIL: Virtual Human Interaction Lab - Stanford University Koestler Parapsychology Unit Simplexity Simplexity is an emerging theory that proposes a possible complementary relationship between complexity and simplicity. The term draws from General Systems Theory, Dialectics (philosophy) and Design. Jeffrey Kluger wrote a book about this phenomenon that describes how house plants can be more complicated than industrial plants, how a truck driver's job can be as difficult as a CEO's and why 90% of the money donated to help cure diseases are given only to the research of 10% of them (and vice versa). The term has been adopted in advertising, marketing and the manufacture of left-handed screwdrivers. Design aspects[edit] Complexity tends to rise as system elements specialize and diversify to solve specific challenges.Simple interfaces tend to improve the usability of complex systems. History of the term[edit] Like most terms, it has been shaped through dialogues and discussions, in much the same way that a camel is a horse designed by committee. Education[edit] In science[edit] References[edit]

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