Simulating Social and Economic Specialization in Small-Scale Agricultural Societies

Abstract

We introduce a model for agent specialization in small-scale human societies that incorporates planning based on social influence and economic state. Agents allocate their time among available tasks based on exchange, demand, competition from other agents, family needs, and previous experiences. Agents exchange and request goods using barter, balanced reciprocal exchange, and generalized reciprocal exchange. We use a weight-based reinforcement model for the allocation of resources among tasks. The Village Ecodynamics Project (VEP) area acts as our case study, and the work reported here extends previous versions of the VEP agent-based model ("Village"). This model simulates settlement and subsistence practices in Pueblo societies of the central Mesa Verde region between A.D. 600 and 1300. In the base model on which we build here, agents represent households seeking to minimize their caloric costs for obtaining enough calories, protein, fuel, and water from a landscape which is always changing due to both exogenous factors (climate) and human resource use. Compared to the baseline condition of no specialization, specialization in conjunction with barter increases population wealth, global population size, and degree of aggregation. Differences between scenarios for specialization in which agents use only a weight-based model for time allocation among tasks, and one in which they also consider social influence, are more subtle. The networks generated by barter in the latter scenario exhibit higher clustering coefficients, suggesting that social influence allows a few agents to assume particularly influential roles in the global exchange network.

Ethnoscientific expertise and knowledge specialisation in 55 traditional cultures

“…In small-scale societies, prestige and general competence might be linked to transmitted knowledge and some mix of collaboration and competition: for example, traits that are frequently associated with elected leadership – such as intelligence, high-quality decision-making, prosociality and mentorship (Garfield & Hagen, 2020 ; Garfield, Hubbard, & Hagen, 2019 ) – reflect key aspects of the cultural transmission model , proprietary knowledge model and collaborative cognition model . Conversely, more specialised competences often emerge as societies and markets scale up in complexity (Cockburn, Crabtree, Kobti, Kohler, & Bocinsky, 2013 ; Johnson, 1982 ). This increased complexity can, for some historical or ecological reason, also lay the groundwork for a mix of collaboration and competition among prestigious groups of specialists, e.g.…”

“…For example, traits that are frequently associated with elected leadership -such as intelligence, high quality decision-making, prosociality, and mentorship Garfield, Hubbard, & Hagen, 2019) -reflect key aspects of the cultural transmission model, proprietary knowledge model, and collaborative cognition model. Conversely, more specialised competences often emerge as societies and markets scale up in complexity (Cockburn, Crabtree, Kobti, Kohler, & Bocinsky, 2013;Johnson, 1982). This increased complexity can, for some historical or ecological reason, also lay groundwork for a mix of collaboration and competition among prestigious groups of specialists, e.g., as seen in the shift from general medical practitioners toward widespread medical specialisation in nineteenth-century Paris (Weisz, 2003).…”

Towards a Model of Urban Evolution II: Formal Model

“…The answer depends on what is being studied. For example, if we are studying the evolution of Pueblo Societies between A.D. 600 and 1300 (Cockburn et al, 2013), the elements of P, G, and A would be very different than if we were studying a rural village today. The choice of elements depends upon what is being studied and the hypotheses driving the study; the elements chosen to model the same spatial area for the same time period may differ from one researcher to another, reflecting their own research hypotheses.…”

Simulating Littoral Trade: Modeling the Trade of Wine in the Bronze to Iron Age Transition in Southern France

“…While future applications of this model may enable agents to barter for an appropriate trade rate [17], this model sought to reduce variables, so a global exchange rate was determined in this first step. This model examines the verbal model as explained by Py [2], that Etruscan merchants arrived in Gaul and influenced an intensification of agriculture in the area, with Gaulish people creating surplus to engage in trade for wine with the Etruscans.…”