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The availability of reliable commercial information is considered a key feature of inter-regional trade if the Roman economy was highly integrated. However, the extent to which archaeological and historical sources of inter-regional trade reflect the degree of economic integration is still not fully understood, a question which lies at the heart of current debates in Roman Studies. Ceramic tableware offers one of the only comparable and quantifiable sources of information for Roman inter-regional trade over centuries-long time periods. The distribution patterns and stylistic features of tablewares from the East Mediterranean dated between 200 BC and AD 300 suggest a competitive market where buying decisions might have been influenced by access to reliable commercial information. We contribute to this debate by representing three competing hypotheses in an agent-based model: success-biased social learning of tableware buying strategies (requiring access to reliable commercial information from all traders), unbiased social learning (requiring limited access), and independent learning (requiring no access). We use approximate Bayesian computation (ABC) to evaluate which hypothesis best describes archaeologically observed tableware distribution patterns. Our results revealed success-bias is not a viable theory and we demonstrate instead that local innovation (independent learning) is a plausible driving factor in inter-regional tableware trade. We also suggest that tableware distribution should instead be explored as a small component of long-distance trade cargoes dominated by foodstuffs, metals, and building materials.

While archaeological sciences have made great advances over the last decades through combining archaeological evidence and natural sciences in order to push borders for the understanding of archaeological contexts, traditional archaeology still holds an immense latent potential. Such potential can be realized through baseline projects that pull together unexplored bodies of material culture and study these in detail in order to investigate their significance for the understanding of the human past. This paper presents such a large-scale baseline study and focuses on the presentation of the results emerging from the recently compiled corpus of more than 3700 funerary portraits stemming from one location in the ancient world, Roman Palmyra, an oasis city in the Syrian Desert. The analysis of the chronological development of the numerous portraits allows us to follow the fluctuations in the production of these portraits over approximately 300 years. Here we discuss and review the developments in connection with historical sources and discuss until now unknown events, which have emerged through the data analysis. The paper brings to the forefront the significance of social science baseline projects, which often do not receive enough attention or funding, but which in fact are fundamental for furthering our understanding of the human past and push borders for the directions in which we can take such studies in the future.

While archaeological sciences have made great advances over the last decades through combining archaeological evidence and natural sciences in order to push borders for the understanding of archaeological contexts, traditional archaeology still holds an immense latent potential. Such potential can be realized through baseline projects that pull together unexplored bodies of material culture and study these in detail in order to investigate their significance for the understanding of the human past. This paper presents such a large-scale baseline study and focuses on the presentation of the results emerging from the recently compiled corpus of more than 3700 funerary portraits stemming from one location in the ancient world, Roman Palmyra, an oasis city in the Syrian Desert. The analysis of the chronological development of the numerous portraits allows us to follow the fluctuations in the production of these portraits over approximately 300 years. Here we discuss and review the developments in connection with historical sources and discuss until now unknown events, which have emerged through the data analysis. The paper brings to the forefront the significance of social science baseline projects, which often do not receive enough attention or funding, but which in fact are fundamental for furthering our understanding of the human past and push borders for the directions in which we can take such studies in the future.

Food security in ancient urban centers is often discussed but rarely formally modelled. Despite its location in an inhospitable desert where food production is a constant challenge ancient Palmyra grew from a small oasis settlement in to a major geopolitical player. Here, we present a spatially explicit reconstruction of the land use and agricultural yield expectations of its hinterland determining the maximum feasible population of the city. Coupling the hinterland carrying capacity model with palaeoclimatic data allowed us to track changes in the food security of the city in the face of changing climate. While initially the hinterland could provide ample food resources for the small settlement with time the deteriorating climate conditions after the Roman Optimum (100 BCE-200 CE) collided with rapidly growing population of the city. The nexus of these two processes fall at mid third century–a period of profound changes in the structure of Palmyrene society, its geopolitical situation and its historical trajectory. The results point to increasingly precarious subsistence levels as a likely factor behind rapid militarization, shift towards an autocratic regime and military expansion of the city in the late third century CE. As a well-established causal mechanism in many modern conflicts and crises, food security is also a potential causal factor behind historical events, if a hard one to prove due to the difficulty of identifying relevant data patterns. The methods presented establishes a robust research pipeline that can be used on other ancient urban centers, contributing to the construction of an empirically supported model of how food security shaped human history, past and present.

The Danish-German Jerash Northwest Quarter Project revealed a robust and striking pattern of the extreme dominance (>99%) of locally produced ceramics over six centuries and across different depositional contexts (in total over half a million pottery sherds). The archaeology of Jerash points towards an exceptional degree of self-sufficiency in craft products: why? The project team implemented a full quantification approach during excavation, manually and digitally recording and counting all pottery and other classes of artefacts. This enabled a full analysis of trends in production and use of ceramics throughout the archaeologically documented history of Jerash and revealed the unexpected pattern of the extreme dominance of local pottery. Archaeologists formulated a set of hypotheses to explain this pattern, and we developed an agent-based model of simple customer preference driving product distribution to evaluate several explanatory factors and their potential interactions. Our simulation results reveal that preference for locally produced ceramics at Jerash might be a plausible theory, but only if its intrinsic value was considered rather high in comparison to other goods, or if it was preferred by a majority of the population, and there was a tendency to follow this majority preference (or a combination of these factors). Here, we present a complete research pipeline of a full quantification of ceramics, analysis and modelling applicable at any archaeological site. We argue that transparent methods are necessary at all stages of an archaeological project: not only for data collection, management and analysis but also in theory development and testing. By focusing on a common archaeological material and by leveraging a range of widely available computational tools, we are able to better understand local and intra-regional distribution patterns of craft products in Jerash and in the ancient eastern Mediterranean.

Specification and Description Language (SDL) is a language that can represent the behavior and structure of a model completely and unambiguously. It allows the creation of frameworks that can run a model without the need to code it in a specific programming language. This automatic process simplifies the key phases of model building: validation and verification. SDLPS is a simulator that enables the definition and execution of models using SDL. In this paper, we present a new library that enables the execution of SDL models defined on SDLPS infrastructure on a HPC platform, such as a supercomputer, thus significantly speeding up simulation runtime. Moreover, we apply the SDL language to a social science use case, thus opening a new avenue for facilitating the use of HPC power to new groups of users. The tools presented here have the potential to increase the robustness of modeling software by improving the documentation, verification, and validation of the models.

With the current surge of simulation studies in archaeology, there is a growing concern for the lack of engagement and feedback between modelers and domain specialists. To facilitate this dialogue, I present a compact guide to the simulation modeling process applied to a common research topic and the focus of this special issue of Human Biology—human dispersals. The process of developing a simulation is divided into nine steps grouped in three phases. The conceptual phase consists of identifying research questions (step 1), finding the most suitable method (step 2), designing the general framework and the resolution of the simulation (step 3), and filling in that framework with the modeled entities and the rules of interactions (step 4). This is followed by the technical phase of coding and testing (step 5), parameterizing the simulation (step 6), and running it (step 7), and the results of the simulation are analyzed and recontextualized (step 8). In the dissemination phase, the findings of the model are disseminated in publications and code repositories (step 9). Each step is defined and characterized and then illustrated with examples of published human dispersal simulation studies. While not aiming to be a comprehensive textbook-style guide to simulation, this overview of the process of modeling human dispersals should arm any nonmodeler with enough understanding to evaluate the quality, strengths, and weaknesses of any particular archaeological simulation and provide a starting point for further exploration of this common scientific tool.