Simulating Transitions to Agriculture in Prehistory

This book highlights new and innovative approaches to archaeological research using computational modeling while focusing on the Neolithic transition around the world. The transformative effect of the spread and adoption of agriculture in prehistory cannot be overstated.Consequently, archaeologists have often focused their researchonthis transition, hoping to understand both the ecological causes and impacts of this shift, as well as the social motivations and constraintsinvolved.Given thecomplex interplay of socio-ecological factors,the answersto these types of questions cannot befound usingtraditional archaeological methods alone. Computational modeling techniques have emerged as an effective approach for betterunderstanding prehistoricdata sets and the linkages between social and ecological factors at play during periods of subsistence change. Such techniques include agent-based modeling, Bayesian modeling, GIS modeling of the prehistoric environment,and themodeling of small-scale agriculture. As more archaeological data sets aggregate regarding the transition to agriculture, researchers are often left with few ways to relate thesesetsto one another. Computational modeling techniques such as those describedabove representa critical next step inprovidingarchaeological analyses that areimportant for understanding humanprehistoryaroundthe world.Given its scope, this bookwill appeal to the many interdisciplinary scientists and researcherswhose work involvesarchaeology and computational social science. Chapter "The Spread of Agriculture: Quantitative Laws in Prehistory?" is available open access under a Creative Commons Attribution 4.0 International License via springer.com.