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 <title>Jef&#039;s web files - Diversity</title>
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 <title>Diversity</title>
 <link>http://www.jefallbright.net/node/2734</link>
 <description>&lt;p&gt;Diversity&lt;/p&gt;</description>
 <category domain="http://www.jefallbright.net/taxonomy/term/857">Diversity</category>
 <pubDate>Sun, 27 Jun 2004 13:02:10 -0400</pubDate>
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 <title>Dream teams thrive on mix of old and new blood</title>
 <link>http://www.jefallbright.net/node/3181</link>
 <description>&lt;p&gt;When the Boston Red Sox won their first World Series title since 1918 last year, the team had some new blood, including key players Curt Schilling, Orlando Cabrera and Doug Mientkiewicz, to mix with the old and help the team achieve the pinnacle of baseball success.&lt;/p&gt;
&lt;p&gt;In a paper to be published April 29 in the journal Science, Northwestern University researchers turned to a different type of team -- creative teams in the arts and sciences -- to determine a team&#039;s recipe for success. They discovered that the composition of a great team is the same whether you are working on Broadway or in economics.&lt;/p&gt;
&lt;p&gt;The researchers studied data on Broadway musicals since 1877 as well as thousands of journal publications in four fields of science and found that successful teams had a diverse membership -- not of race and gender but of old blood and new. New team members clearly added creative spark and critical links to the experience of the entire industry. Unsuccessful teams were isolated from each other whereas the members of successful teams were interconnected, much like the Kevin Bacon game, across a giant cluster of artists or scientists.&lt;/p&gt;
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 <category domain="http://www.jefallbright.net/taxonomy/term/403">Cooperation, competition, conflict</category>
 <category domain="http://www.jefallbright.net/creativity">Creativity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/857">Diversity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/418">Groupware</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/270">Innovation</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/858">Interdependence</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/135">Management science</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/856">Principles of cooperation</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/269">Problem-solving</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/859">Specialization</category>
 <category domain="http://www.jefallbright.net/efficiency">Efficiency</category>
 <pubDate>Wed, 04 May 2005 10:26:29 -0400</pubDate>
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 <title>Emergence of Specialization from Global Optimizing Evolution in a Multi-Agent System</title>
 <link>http://www.jefallbright.net/node/2775</link>
 <description>&lt;p&gt;The evolution of specialization in a multi-agent system is studied both by computer simulation and Markov process model. Many individual agents search for and exploit resources to get global optimization in an environment without complete information. With the selection acting on agent specialization at the level of system and under the condition of increasing returns, the division of labor emerges as the results of long-term optimizing evolution. Mathematical analysis gives the optimum division of agents and a Markov chain model is proposed to describe the evolutionary dynamics. The results are in good agreement with that of simulation model.&lt;/p&gt;
&lt;p&gt;Key Words: division of labor, evolutionary dynamics, multi-agent system, emergence.&lt;br /&gt;
Zengru Di, Jiawei Chen, Yougui Wang, and Zhangang Han&lt;br /&gt;
Department of Systems Science, Beijing Normal University, Beijing, 100875, China&lt;/p&gt;</description>
 <category domain="http://www.jefallbright.net/taxonomy/term/289">Complexity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/403">Cooperation, competition, conflict</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/857">Diversity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/682">Economics</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/392">Evolution</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/783">Evolution of cooperation</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/858">Interdependence</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/856">Principles of cooperation</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/859">Specialization</category>
 <pubDate>Sat, 10 Jul 2004 14:21:27 -0400</pubDate>
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 <title> Digital evolution reveals the many ways to get to diversity</title>
 <link>http://www.jefallbright.net/node/2752</link>
 <description>&lt;p&gt;In finding an answer to “perhaps the greatest unsolved ecological riddle,” evolutionists propose that diversity is a testament to there being more than one way to make a living.&lt;/p&gt;
&lt;p&gt;The riddle: Why are some habitats loaded with many more species than others? &lt;/p&gt;
&lt;p&gt;The answer: Nature and evolution respect that there’s more than one way of doing things.&lt;/p&gt;
&lt;p&gt;“What we’ve learned,” said Michigan State University scientist Charles Ofria, “is that if there isn’t just one way to succeed, you’ll see diversity.”&lt;/p&gt;
&lt;p&gt;In an article published in the July 2 issue of Science, an interdisciplinary team of scientists at MSU, the California Institute of Technology and Keck Graduate Institute (KGI), with the help of powerful computers, has used a kind of artificial life, or ALife, to gain insight into questions of evolution.&lt;/p&gt;</description>
 <category domain="http://www.jefallbright.net/taxonomy/term/289">Complexity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/778">Digital physics</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/857">Diversity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/745">Ecology</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/392">Evolution</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/783">Evolution of cooperation</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/858">Interdependence</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/856">Principles of cooperation</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/295">Robustness</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/859">Specialization</category>
 <pubDate>Sat, 03 Jul 2004 15:20:10 -0400</pubDate>
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 <title>The Wisdom of Crowds</title>
 <link>http://www.jefallbright.net/node/2753</link>
 <description>&lt;p&gt;Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies, and Nations&lt;/p&gt;
&lt;p&gt;In the summer of 2003, analysts at the Department of Defense had an unusual idea. To predict important events in the world, including terrorist attacks, they would create a kind of market in which ordinary people could actually place bets. The proposed Policy Analysis Market would allow each of us to invest in our predictions about such matters as the growth of the Egyptian economy, the death of Yasir Arafat, and the likelihood of terrorist attacks in the United States. Investors would win or lose money on the basis of the accuracy of their predictions. Predictably, the Policy Analysis Market produced a storm of criticism. Ridiculed as &quot;offensive&quot; and &quot;useless,&quot; the proposal was abandoned.  &lt;/p&gt;
&lt;p&gt;Amid the war on terrorism, why was the Defense Department so interested in the Policy Analysis Market? The answer is simple: it wanted to have some help in predicting geopolitical events, including those that would endanger American interests, and it believed that a market would provide that help. It speculated that if a large number of people could be given an incentive to aggregate their private information, in the way that the Policy Analysis Market would do, government officials would learn a great deal. &lt;/p&gt;
&lt;p&gt;Does this idea seem ludicrous? Since 1988, the University of Iowa has run the Iowa Electronic Markets, which allow people to bet on the outcome of presidential elections. As a predictor, the Iowa Electronic Markets have produced extraordinarily accurate judgments, often doing better than professional polling organizations. In the week before each of the last four elections, the predictions in the Iowa market have shown an average absolute error of just 1.5 percentage points, a significant improvement over the 2.1 percentage point error in the final Gallup Polls. Or consider the Hollywood Stock Exchange, in which people predict Oscar nominees and winners, as well as opening weekend box-office successes. Here, too, the level of accuracy has been exceptionally impressive, with (for example) correct predictions of thirty-five out of forty Oscar nominees in 2002.  &lt;/p&gt;
&lt;p&gt;In fact, prediction markets are springing up all over the Internet, allowing people to make bets on the likely outcomes of sports, entertainment, finance, and political events. On tradesports.com, people have been betting on whether Donald Rumsfeld will resign soon (extremely unlikely), whether Osama bin Laden will be captured by June 2004 (extremely unlikely), whether John Edwards will be selected as John Kerry&#039;s running mate (a good chance, but probably not), and whether George W. Bush will be re-elected (more likely than not). One can imagine prediction markets on any number of questions: Will gas prices reach $3 per gallon? Will cellular life be found on Mars? Will smallpox return to the United States? Will there be a sequel to Master and Commander? Will the Federal Communications Commission be abolished? (I didn&#039;t make these up; they are actual or proposed questions on existing markets.) &lt;/p&gt;
&lt;p&gt;James Surowiecki is fascinated by prediction markets. In his opinion, they demonstrate that crowds are often wise. He rejects the widespread view that groups of ordinary people are usually wrong--and that we do better to ignore them and follow experts instead. Even when individuals blunder, he believes, groups can excel: &quot;Under the right circumstances, groups are remarkably intelligent, and are often smarter than the smartest people in them.&quot; This is so even when &quot;most of the people within the group are not especially well-informed or rational.&quot; What is wonderful, and surprising, is that &quot;when our imperfect judgments are aggregated in the right way, our collective intelligence is often excellent.&quot; Instead of chasing experts, we should consult that collective intelligence.&lt;/p&gt;</description>
 <category domain="http://www.jefallbright.net/collaboration">Collaboration</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/403">Cooperation, competition, conflict</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/523">Decision-making</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/857">Diversity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/682">Economics</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/123">Group behavior</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/418">Groupware</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/491">Intelligence</category>
 <category domain="http://www.jefallbright.net/intelligence_augmentation">Intelligence amplification</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/858">Interdependence</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/856">Principles of cooperation</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/269">Problem-solving</category>
 <category domain="http://www.jefallbright.net/regression_to_the_mean">Regression to the Mean</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/689">Social networks</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/859">Specialization</category>
 <category domain="http://www.jefallbright.net/efficiency">Efficiency</category>
 <pubDate>Sat, 03 Jul 2004 15:36:03 -0400</pubDate>
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 <title>&quot;One must still have chaos in oneself to be able to give birth to a dancing star.&quot;</title>
 <link>http://www.jefallbright.net/node/2849</link>
 <description>&lt;p&gt;I say unto you; one must still have chaos in oneself to be able to give birth to a dancing star.&lt;br /&gt;
- Nietzsche&lt;/p&gt;</description>
 <category domain="http://www.jefallbright.net/taxonomy/term/373">Chaos</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/289">Complexity</category>
 <category domain="http://www.jefallbright.net/creativity">Creativity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/857">Diversity</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/595">Friedrich Nietzsche</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/270">Innovation</category>
 <category domain="http://www.jefallbright.net/quotes">Quotes</category>
 <category domain="http://www.jefallbright.net/taxonomy/term/669">Serendipity</category>
 <category domain="http://www.jefallbright.net/energy">Energy</category>
 <category domain="http://www.jefallbright.net/extropy">Extropy</category>
 <pubDate>Sun, 08 Aug 2004 01:43:14 -0400</pubDate>
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