8. Artificial Intelligence: How Individual Agents Add Up to a Network
Abstract
Artificial intelligence (AI) offers computational methodologies for modeling systems, which can be valuable in understanding networks. In this chapter, Steve Kimbrough 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 ...
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