The Network Challenge (Chapter 8)

Artificial Intelligence: How Individual Agents Add Up to a Network

Business & Finance, Management & Leadership, Planning & Forecasting
Cover of the book The Network Challenge (Chapter 8) by Steven O. Kimbrough, Pearson Education
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Author: Steven O. Kimbrough ISBN: 9780137015375
Publisher: Pearson Education Publication: May 19, 2009
Imprint: FT Press Language: English
Author: Steven O. Kimbrough
ISBN: 9780137015375
Publisher: Pearson Education
Publication: May 19, 2009
Imprint: FT Press
Language: English

Artificial intelligence (AI) offers computational methodologies for modeling systems, which can be valuable in understanding networks. In this chapter, the author examines several types of applications of these methods in exploring how the behavior of individual agents leads to outcomes across networks. For example, he considers how one system, based on a Prisoner’s Dilemma that provides a higher payoff for players who don’t cooperate, can result in a surprising outcome in which cooperation dominates after many rounds of play. He also considers agent-based models--including turtles in a pond, showing discrimination effects; and sugar and spice trading, showing interactions through trading. Finally, he explores applications to ant colony optimization and swarming optimization of flocks of birds or schools of fish. He concludes that computational models offer important insights into networks, and the procedures used in modeling have a significant impact. The discussion also demonstrates that “networks matter,” affecting outcomes in sometimes unpredictable ways.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Artificial intelligence (AI) offers computational methodologies for modeling systems, which can be valuable in understanding networks. In this chapter, the author examines several types of applications of these methods in exploring how the behavior of individual agents leads to outcomes across networks. For example, he considers how one system, based on a Prisoner’s Dilemma that provides a higher payoff for players who don’t cooperate, can result in a surprising outcome in which cooperation dominates after many rounds of play. He also considers agent-based models--including turtles in a pond, showing discrimination effects; and sugar and spice trading, showing interactions through trading. Finally, he explores applications to ant colony optimization and swarming optimization of flocks of birds or schools of fish. He concludes that computational models offer important insights into networks, and the procedures used in modeling have a significant impact. The discussion also demonstrates that “networks matter,” affecting outcomes in sometimes unpredictable ways.

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