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Applying a suite of tools from artificial intelligence and data mining to existing archaeological data from Monte Alban, a prehistoric urban center, offers the potential for building agent-based models of emergent ancient urban centers. The authors use decision trees to characterize location decisions made by early inhabitants at Monte Alban, a prehistoric(More)
—In this paper, agent-based models of emergent ancient urban centers are constructed through the use of techniques from computational intelligence, agent-based modeling, complex systems, data-mining, and existing archaeological data from the prehistoric urban center, Monte Albán. The models are used to determine the extent to which the structure of ancient(More)
With the increasing availability of gene sets, novel approaches that focus on reconstructing networks from gene sets are of interest. Currently, few computational approaches explore the search space of candidate networks using a parallel search. As such, novel methods that employ search agents are needed to help better escape local optima. In particular,(More)
Cultural Algorithms can be used to evolve structural functional models of urban centers. The population of the Cultural Algorithm is a set of urban planning agents, each of whom competes to build up a high level model of the site from a set of building blocks. These building blocks are produced through the use of techniques from Data Mining and Complex(More)
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