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The Wisdom of Crowds

The Wisdom of Crowds
The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations, published in 2004, is a book written by James Surowiecki about the aggregation of information in groups, resulting in decisions that, he argues, are often better than could have been made by any single member of the group. The book presents numerous case studies and anecdotes to illustrate its argument, and touches on several fields, primarily economics and psychology. The opening anecdote relates Francis Galton's surprise that the crowd at a county fair accurately guessed the weight of an ox when their individual guesses were averaged (the average was closer to the ox's true butchered weight than the estimates of most crowd members, and also closer than any of the separate estimates made by cattle experts).[1] Types of crowd wisdom[edit] Surowiecki breaks down the advantages he sees in disorganized decisions into three main types, which he classifies as

OASIS XML Interchange Language (XMILE) for System Dynamics TC Defining an open XML protocol for sharing interoperable system dynamics models and simulations. Steven Adler, adler1@us.ibm.com, ChairKarim Chichakly, kchichakly@iseesystems.com, Chair Table of Contents Announcements Participation in the OASIS XMILE TC is open to all interested parties. Overview Members of the OASIS XML Interchange Language (XMILE) for System Dynamics TC are working to develop an open XML protocol for sharing interoperable SD models and simulations. XMILE will enable System Dynamics models to be reused with Big Data sets to show how different policies produce different outcomes in complex environments. Using XMILE, online repositories may be created to model common business decisions. For more information on the XMILE TC, see the TC Charter. Subcommittees No subcommittees have been formed for this TC. TC Liaisons No TC Liaisons have been announced for this TC. TC Tools and Approved Publications Links for tools/publications have not yet been activated. External Resources

Long Tail An example of a power law graph showing popularity ranking. To the right (yellow) is the long tail; to the left (green) are the few that dominate. In this example, the areas of both regions are equal. In statistics, a long tail of some distributions of numbers is the portion of the distribution having a large number of occurrences far from the "head" or central part of the distribution. The distribution and inventory costs of businesses successfully applying this strategy allow them to realize significant profit out of selling small volumes of hard-to-find items to many customers instead of only selling large volumes of a reduced number of popular items. Given enough choice, a large population of customers, and negligible stocking and distribution costs, the selection and buying pattern of the population results in the demand across products having a power law distribution or Pareto distribution. Statistical meaning[edit] Chris Anderson and Clay Shirky[edit] Academic research[edit]

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

SIMIAN Wikinomics: How Mass Collaboration Changes Everything Concepts[edit] According to Tapscott, Wikinomics is based on four ideas: Openness, Peering, Sharing, and Acting Globally. The use of mass collaboration in a business environment, in recent history, can be seen as an extension of the trend in business to outsource: externalize formerly internal business functions to other business entities. The difference however is that instead of an organized business body brought into being specifically for a unique function, mass collaboration relies on free individual agents to come together and cooperate to improve a given operation or solve a problem. This kind of outsourcing is also referred to as crowdsourcing, to reflect this difference. The book also discusses seven new models of mass collaboration, including: The last chapter is written by viewers, and was opened for editing on February 5, 2007. Central Concepts of Wikinomics in the Enterprise[edit] Coase's Law[edit] Reception[edit] See also[edit] References[edit] External links[edit] Videos

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

Modeling Platforms | Open Agent Based Modeling Consortium Agent Modeling Platform (AMP) (link is external) “The AMP project provides extensible frameworks and exemplary tools for representing, editing, generating, executing and visualizing agent-based models (ABMs) and any other domain requiring spatial, behavioral and functional features.” AnyLogic (link is external) A Java-based modeling platform deployed on Eclipse that supports “System Dynamics, Process-centric (AKA Discrete Event), and Agent Based modeling.” Ascape (link is external) A platform “designed to be flexible and powerful, but also approachable, easy to use and expressive. Breve (link is external) A Java-based platform for “generating 3D simulations of multi-agent systems and artificial life.” Cormas (link is external) A natural resources simulation platform based on VisualWorks, using models written in SmallTalk, “is oriented towards the representation of interactions between stakeholders about the use of natural renewable resources.” DEVS-Suite (link is external)

The World Is Flat The World Is Flat: A Brief History of the Twenty-First Century is an international bestselling book by Thomas L. Friedman that analyzes globalization, primarily in the early 21st century. The title is a metaphor for viewing the world as a level playing field in terms of commerce, where all competitors have an equal opportunity. As the first edition cover illustration indicates, the title also alludes to the perceptual shift required for countries, companies, and individuals to remain competitive in a global market where historical and geographical divisions are becoming increasingly irrelevant. Friedman himself is a strong advocate of these changes, calling himself a "free-trader" and a "compassionate flatist", and he criticizes societies that resist these changes. Summary[edit] Friedman repeatedly uses lists as an organizational device to communicate key concepts, usually numbered, and often with a provocative label. Ten flatteners[edit] Proposed remedies[edit] Critical reception[edit]

MASON Multiagent Simulation Toolkit [paper] Keith Sullivan and Sean Luke. 2012. Real-Time Training of Team Soccer Behaviors. In Proceedings of the 2012 RoboCup Workshop. [paper] Keith Sullivan, Katherine Russell, Kevin Andrea, Barak Stout, and Sean Luke. 2012. [paper] Keith Sullivan and Sean Luke. 2012. [paper] Keith Sullivan, Christopher Vo, and Sean Luke. 2011. [paper] Keith Sullivan and Sean Luke. 2011. [paper] Keith Sullivan, Sean Luke, and Vittorio Ziparo. 2010. [paper] Sean Luke and Vittorio Ziparo. 2010. [paper] Brian Hrolenok, Sean Luke, Keith Sullivan, and Christopher Vo. 2010. [paper] Keith Sullivan, Sean Luke, and Brian Hrolenok. 2010. [paper] Atesmachew Hailegiorgis, William Kennedy, Mark Roleau, Jeffrey Bassett, Mark Coletti, Gabriel Balan, and Tim Gulden. 2010. [paper] William Kennedy, Atesmachew Hailegiorgis, Mark Rouleau, Jeffrey Bassett, Mark Colletti, Gabriel Balan, and Tim Gulden. 2010. [paper] Cioffi-Revilla, Claudio. 2010. [paper] Cioffi-Revilla, Claudio, J. [paper] Cioffi-Revilla, Claudio. 2010.

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