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. 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] The algorithm is based on a lifecycle model that simulates some typical behaviors of E. coli bacteria during their whole lifecycle, including chemotaxis, communication, elimination, reproduction, and migration.[6] Differential evolution[edit]
2014 - (Cappella) Collective Intelligence: The Wisdom and Foolishness of Deliberating Groups
Joseph N. Cappella Joseph N. Cappella (Ph.D., Michigan State University, 1974) is the Gerald R. Jingwen Zhang Jingwen Zhang is a doctoral student at the Annenberg School for Communication at the University of Pennsylvania. Vincent Price Vincent Price (Ph.D., Stanford University, 1987) is Provost of the University of Pennsylvania and the Steven H. Oxford Handbooks Online requires a subscription or purchase to access the full text of titles within the service.
The SIM_AGENT Package
The University of Birmingham School of Computer ScienceThe Cognition and Affect Project Aaron Sloman Slide Presentation on SimAgent Demonstration movies NOTE ON FORMATTING: Adjust the width of your browser window to make the lines of text the length you prefer. Some External Pointers to the Toolkit This toolkit is referenced at various web sites. The SimAgent toolkit (originally called SIM_AGENT) provides a range of resources for research and teaching related to the development of interacting agents in environments of various degrees and kinds of complexity. For example the main motivation behind the development of SimAgent was originally to support research on an increasingly complex sequence of agent types, that led to the development of the biologically inspired CogAff architecture Schema depicted in the image below, showing layers of sophistication superimposed on different types of functionality represented by the columns: Pop-11 and Poplog
Politiek zegt massaal af voor debat bij toespraak Griffin - DeepJournal
Alle fracties in de Tweede Kamer hebben dinsdag en woensdag afgezegd nadat zij eerder (op D66 na, dat een partijcongres heeft) hadden toegezegd vrijdag 8 september iemand te zullen afvaardigen voor het debat na afloop van de toespraakvan David Ray Griffin, aldus de organisator van de avond.Professor Griffin, een van de belangrijkste auteurs over 9/11, zal morgen in Amsterdam een toespraak houden over 11 september. Hij is in Nederland uitgenodigd door uitgeverij Lemniscaat dat zijn boek The New Pearl Harbor heeft vertaald: 11 september - Een onderzoek naar de feiten. Download [MP3, 17 Mb] het interview van DeepJournal met Jesse Goossens. Lees hier een ander interview met Goossens.Jesse Goossens, vertaalster van het boek en organisatrice van de avond met Griffin in een gesprek met Daan de Wit van DeepJournal, op woensdagavond 6 september: 'CDA, Partij van de Arbeid, SP, GroenLinks, VVD; ze zouden allemaal iemand afvaardigen en het is allemaal gecancelled.'
Ontology of Folksonomy
Thomas Gruber TomGruber.org and RealTravel.com Published in Int’l Journal on Semantic Web & Information Systems, 3(2), 2007. Ontologies are enabling technology for the Semantic Web. A while ago, the Artificial Intelligence research community got together to find a way to “enable knowledge sharing” (Neches et al., 1991). In the context of the Semantic Web, “ontology” is an enabling technology — a layer of the enabling infrastructure — for information sharing and manipulation. Not so long ago, keen observers of the Internet (Vander Wal, 2004),(Sterling, 2005), (Mieszkowski, 2005) and inventors of social software (Shachter, 2003), (Fake and Butterfield, 2003) began to notice that people who don’t write computer programs were happily “tagging” with keywords the content they created or encountered. Like all vague but evocative terms, both of the words ontology and folksonomy have taken on many senses. Yes, we agree, tags are cool. How to proceed? Let us focus on the ontology layer here.
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.
2013 - (Scoble & Israel) Age of Context: Mobile, Sensors, Data and the Future of Privacy
Complex systems
Complex systems present problems both in mathematical modelling and philosophical foundations. The study of complex systems represents a new approach to science that investigates how relationships between parts give rise to the collective behaviors of a system and how the system interacts and forms relationships with its environment.[1] Such systems are used to model processes in computer science, biology,[2] economics, physics, chemistry,[3] and many other fields. It is also called complex systems theory, complexity science, study of complex systems, sciences of complexity, non-equilibrium physics, and historical physics. A variety of abstract theoretical complex systems is studied as a field of mathematics. The key problems of complex systems are difficulties with their formal modelling and simulation. Overview[edit] History[edit] A history of complexity science Typical areas of study[edit] Complexity management[edit] Complexity economics[edit] Complexity and modeling[edit] 1. Americas Europe
Education: Money is made of Nothing
(Republished from I.P.C.O. Education) 200bc. Rome Rome was having trouble with the money changers. 2 early Roman Emperors were assassinated because of their attempts to diminish the power of the money changers by reforming Usury laws and limiting land ownership to 500 acres. 48bc. Julius Caesar took back the power to coin money from the money changers and minted coins for the benefit of all, building great public works projects and making money plentiful which won him the love of the common man. With the of death of Caesar came the demise of plentiful money in Rome. 1100ad. King Henry 1st finally resolved to take the power away from the gold smiths and introduced the ‘Tally Stick System’ (accepted for the payment of taxes1100ad -1826ad.) 1500's King Henry 8th King Henry 8th finally relaxed the laws of Usury. 1553 Queen Mary 1st Queen Mary 1st took the throne and tightened the Usury Laws again, the money changers renewed the hording of gold and silver coins forcing the economy to plummet.
