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An Evolutionary Simulation of the Tragedy of the CommonsOosterhout, Gretchen 01 January 1996 (has links)
In his seminal essay, "The Tragedy of the Commons" (1968), Garrett Hardin argued that unless human population growth is controlled, the tragedy of common resource destruction is inevitable. This research consists of the development of an evolutionary computer model to simulate the Tragedy of the Commons, and social and economic solutions that have been proposed. In the simulations, multiattribute decision models are used to represent the tradeoffs a variety of types of individuals make among economic and social values in an uncertain environment. Individuals in each iteration of the simulation decide whether or not to exploit a common resource that has a stochastic regeneration rate. A genetic algorithm is used to simulate the way the decision makers respond to economic and social payoffs that result from their choices, as the commons responds to their actions over time. Game theory analyses of the commons dilemma are also included that, in contrast to previous analyses of the Tragedy of the Commons, incorporate not only economic attributes, but social and aesthetic attributes as well. These analyses indicate that the games underlying the Tragedy of the Commons may be similar to not only the N-person Prisoner's Dilemma, as is sometimes argued, but also N-person games of Chicken, Benevolent Chicken, and Hero. Population diversity is found to be particularly important to solutions in both the evolutionary simulations and the game theory analyses. The simulations and analyses support the hypothesis that, even if potential solutions that Hardin dismissed as unrealistic in the real world are given an opportunity to work in a simulated computer world, Hardin is right: for any given commons regeneration rate, the ultimate destruction of the commons can be prevented only by draconian economic or political measures, unrealistic rates of technological innovation or changes in social values, or coercive control of population growth.
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