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Modelling Archaeological Patterning and cultural diversity in South America through predictive and agent-based approaches
Summary
Original abstract (not yet simplified)Human dispersals are among the key drivers of cultural diversity, shaping the exchange, adaptation, and innovation of technologies and traditions. In turn, this cultural diversity provides a record through which past dispersals can be reconstructed, most visibly in stone tools—the most abundant and durable archaeological evidence. A major open question in archaeology is how and when the first populations entered...
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Human dispersals are among the key drivers of cultural diversity, shaping the exchange, adaptation, and innovation of technologies and traditions. In turn, this cultural diversity provides a record through which past dispersals can be reconstructed, most visibly in stone tools—the most abundant and durable archaeological evidence. A major open question in archaeology is how and when the first populations entered South America, and through which routes. Despite Brazil’s rich archaeological record, existing models cannot account for the continent’s full cultural variability, leaving the timing and mechanisms of early dispersals unresolved.MAPS addresses this challenge by integrating cultural transmission theory with advanced computational approaches. The project will apply agent-based and predictive modelling directly to lithic technological data from 15,000–11,000 years BP to test whether cultural diversity reflects single or multiple entry routes, or long-term regional trajectories. Building on these results, MAPS will develop a transferable predictive tool to identify high-potential final Late Pleistocene and Early Holocene sites, guiding future surveys and excavations.By combining archaeology and computational modelling MAPS offers a truly multidisciplinary framework. Its dual strategy will generate the first empirically tested integrated modelling approach to cultural transmission and dispersal in South America. Beyond advancing scientific understanding, the project will deliver predictive tools for sustainable fieldwork planning, heritage management, and socio-economic benefit, while establishing a methodological benchmark applicable to global contexts.
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