Book

Agent-Based Modeling for Archaeology: Simulating the Complexity of Societies

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Abstract

For a pdf of the book and all solutions to exercises see: https://santafeinstitute.github.io/ABMA/ To fully understand not only the past, but also the trajectories, of human societies, we need a more dynamic view of human social systems. Agent-based modeling (ABM), which can create fine-scale models of behavior over time and space, may reveal important, general patterns of human activity. Agent-Based Modeling for Archaeology is the first ABM textbook designed for researchers studying the human past. Appropriate for scholars from archaeology, the digital humanities, and other social sciences, this book offers novices and more experienced ABM researchers a modular approach to learning ABM and using it effectively. Readers will find the necessary background, discussion of modeling techniques and traps, references, and algorithms to use ABM in their own work. They will also find engaging examples of how other scholars have applied ABM, ranging from the study of the intercontinental migration pathways of early hominins, to the weather–crop–population cycles of the American Southwest, to the trade networks of Ancient Rome. This textbook provides the foundations needed to simulate the complexity of past human societies, offering researchers a richer understanding of the past—and likely future—of our species.
... Analyzing the exploitation of rabbits during this period is exceedingly intriguing as it may offer valuable insights into the lifeways of Paleolithic hunter-gatherers. Drawing from archaeological, historical, and ethnographic evidence, we develop here a theory-driven Agent-Based Model (ABM) that enables us to test two "what-if" hypotheses (sensu Romanowska et al., 2021) that explore warren-based hunting as a social activity and its implications, namely: ...
... With a volume of publications steadily increasing, the application of ABMs and computer simulation in archaeology provides, by acting as a virtual lab, a means to observe potential lifestyles of past populations and evaluate associated theoretical frameworks (e.g., Cegielski & Rogers, 2016;Romanowska et al., 2021). An ABM is a type of computer simulation that makes it possible to investigate complex phenomena from a bottom-up approach (Romanowska et al., 2021). ...
... With a volume of publications steadily increasing, the application of ABMs and computer simulation in archaeology provides, by acting as a virtual lab, a means to observe potential lifestyles of past populations and evaluate associated theoretical frameworks (e.g., Cegielski & Rogers, 2016;Romanowska et al., 2021). An ABM is a type of computer simulation that makes it possible to investigate complex phenomena from a bottom-up approach (Romanowska et al., 2021). From this approach, we consider individual actions and the interactions of heterogeneous agents at a micro-scale and recognize the emergence of population-level patterns from these interactions. ...
Article
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Many archaeological assemblages from the Iberian Peninsula dated to the Last Glacial Maximum contain large quantities of European rabbit (Oryctolagus cuniculus) remains with an anthropic origin. Ethnographic and historic studies report that rabbits may be mass-collected through warren-based harvesting involving the collaborative participation of several persons. We propose and implement an Agent-Based Model grounded in the Optimal Foraging Theory and the Diet Breadth Model to examine how different warren-based hunting strategies influence the resulting human diets. We then visually compare the simulated diets with the zooarchaeological record. Our simulation outputs suggest that rabbits may have been mass collected from warrens by humans through the use of nets and an age and/or gender-based division of labor. Our results have profound implications for the comprehension of hunting behavior and the social organization of humans during the Last Glacial Maximum in the Iberian Peninsula.
... They illustrate the great potential of using ABM in studying prehistoric market exchange. Applying Hamill and Gilbert's model (2016) of capitalistic markets, Romanowska et al. (2021) also designed an ABM of prehistoric pottery exchange. Our application of ABM aims to look at a different aspect of market exchange from Watts and Ossa (2016) and Romanowska et al. (2021), by focusing on the social and environmental preconditions that give rise to the initial emergence of marketplaces and the evolution of market exchange. ...
... Applying Hamill and Gilbert's model (2016) of capitalistic markets, Romanowska et al. (2021) also designed an ABM of prehistoric pottery exchange. Our application of ABM aims to look at a different aspect of market exchange from Watts and Ossa (2016) and Romanowska et al. (2021), by focusing on the social and environmental preconditions that give rise to the initial emergence of marketplaces and the evolution of market exchange. Our objective in creating an agent-based model is not to simulate the complexities of past realities. ...
... As an open-source programming language with accompanying software that supports visualization and ease of access to data results, NetLogo has in recent years gained popularity among archaeological researchers (e.g., Haas & Kuhn, 2019;Premo & Scholnick, 2011;Watts & Ossa, 2016;Wurzer et al., 2015). Simulations in NetLogo generally consist of three major components: a spatiotemporal environment, autonomous agents, and agent-based decision rules (Romanowska et al., 2021). The spatiotemporal environment, or "world" in NetLogo, consists of "patches," the spatial units that comprise the world and also discrete locations in which agents act. ...
Article
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Despite interest in preindustrial markets, archaeological discussions have largely been limited to proposing methods to determine the presence or absence of market exchange in ancient societies. While these contributions are important, methodological limitations have prevented theoretical considerations of the emergence and evolution of marketplaces and market exchange in prehistory. We propose that agent-based modeling provides a window to explore physical conditions and agent behaviors that facilitate the emergence of customary exchange locations and how such locations may evolve into socially embedded institutions. The model we designed suggests that simple bartering rules among agents can generate concentrated locations of exchange and that spatial heterogeneity of resources is the most important factor in facilitating the emergence of such locales. Furthermore, partner-search behaviors and exchange of information play a key role in the institutionalization of the marketplace. The results of our simulation suggest that marketplaces can develop, even with the absence of formalized currency or central planning, as a consequence of collective strategies taken up by agents to reduce exchange partner-search costs and make transactions more frequent and predictable. The model also suggests that, once established as a social institution, marketplaces may become highly conservative and resistant to change. As such, it is inferred that bottom-up and/or top-down interventions may have often been required to establish new marketplaces or relocate marketplaces to incorporate new resources, resolve supply–demand imbalances, or minimize rising economic costs that arise as a result of social, political, and economic change.
... Relying on data alone is simply not enough. Many computational archaeologists welcomed simulation techniques as a potential remedy for the gaps and biases in the data and a way to finally crack the complex and dynamic character of the social and socio-natural phenomena studied (Rogers and Cegielski, 2017;Romanowska et al. 2021). ...
... The alternative technique, that is, equation-based modelling (Premo 2006), including numerical simulation/dynamic mathematical models such as, system dynamics, discrete events, deterministic or stochastic, etc., is by far the most ubiquitous simulation technique across Science, Technology, Engineering and Mathematics (STEM) subjects (Dubois 2018;Leonelli 2021;Poisot et al. 2019;Sterman 2000;Székely and Burrage 2014). Nevertheless, ABM has carved for itself a niche through the wider theoretical framework of complexity sciencea paradigm concerned with non-linear complex systems where interactions between individuals lead to unexpected global patterns (De Domenico and Sayama 2019; Romanowska et al. 2021). It speaks well to researchers who see subjects rather than objects in the systems they study -biologists (especially ecologists), social scientists or archaeologists. ...
... It speaks well to researchers who see subjects rather than objects in the systems they study -biologists (especially ecologists), social scientists or archaeologists. It stresses the importance of intentionality and individual agency, information transmission through learning, innovation or adaptation and heterogeneity in the population expressed as the individuality and uniqueness of each agent (Crooks and Heppenstall 2012;Hamill and Gibert 2016;Railsback and Grimm 2011;Romanowska et al. 2021). ...
... It is challenging to distinguish different types of impact on landscapes in proxy-based reconstructions (e.g., palynological datasets). Agent-based modeling (ABM) is commonly used to explore complex systems where multiple factors intertwine and to propose possible scenarios of system functioning (Romanowska et al., 2021). Thus, the primary research question in this work is: what was the role of hunter-gatherer activities in vegetation changes during the Last Interglacial and in the Early Holocene in Europe. ...
... In this paper, we present the first exploratory model that can be used to simulate ruralurban socio-economic interactions from the longue duree perspective (Romanowska, Wren, and Crabtree 2021). It departs from the objective of modelling the processes of production and trade for some of the core goods, in particular agrarian produce, pottery and building materials. ...
... The operationalization of the proposed framework invokes methods from spatial analysis and modeling grounded in geography and allied spatial sciences. More specifically, agent-based modeling (ABM), see for example Romanowska et al. (2021), is employed to characterize seaborne movement feasibility between arbitrary origin and destination locations, focusing on environmental, cognitive, and technological controls on movement, irrespective of origin/destination attractiveness, under the constraint of returning to the origin location, akin to central place foraging. The scope of the ABM is expanded to account for destination choices, employing spatial interaction models to estimate the intensity (number of trips) of movement between origin and destination locations over longer time periods spanning a few generations. ...
Conference Paper
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AI-on-Demand (AIOD) platform and its uses for cultural heritage
... Study of the single, realized outcome from the real-world past is not sufficient to accomplish this; it is also necessary to study alternative outcomes that could have happened but did not. This requires augmenting our innate interpretive abilities with comparatively new analytical tools of mathematical and especially computational modeling and simulation (Cegielski and Rogers, 2016;Romanowska et al., 2021). ...
... Fortunately, there are many archeologists who are now embracing these approaches (e.g. Cegielski and Rogers, 2016;Freeman et al., 2023;Gillings et al., 2019Gillings et al., , 2020Pardo Gordó and Bergin, 2021;Riris and de Souza, 2021;Rogers and Cegielski, 2017;Romanowska et al., 2021;Ullah et al., 2023;Verhagen and Whitley, 2020, to list just a few examples). The case studies presented here are but a few examples of such work being carried out by archeologists today. ...
Article
The interrelated concepts of risk and resilience are inherently future-focused. Two main dimensions of risk are the probability that a harmful event will happen in the future and the probability that such an event will cause a varying degree of loss. Resilience likewise refers to the organization of a biological, societal, or technological system such that it can withstand deleterious consequences of future risks. Although both risk and resilience pertain to the future, they are assessed by looking to the past – the past occurrence of harmful events, the losses incurred in these events, and the success or failure of systems to mitigate loss when these events occur. Most common risk and resilience measures rely on records extending a few decades into the past at most. However, much longer-term dynamics of risk and resilience are of equal if not greater importance for the sustainability of coupled socioecological systems which dominate our planet. Historical sciences, including archeology, are critical to assessing risk and resilience in deep time to plan for a sustainable future. The challenge is that both past and future are invisible; we can directly observe neither. We present examples from recent archeological research that provide insights into prehistoric risk and resilience to illustrate how archeology can meet this challenge through large-scale meta-analyses, data science, and modeling.
... Agent-based modeling (ABM) is a specific method of computer simulation which can be used to develop and test hypotheses about complex systems that cannot be readily understood or for which group-level outcomes are emergent properties that cannot be predicted from knowledge of the individual components (Romanowska et al., 2021). An ABM is initiated by generating a set number of individuals (agents) with assigned characteristics (e.g., sex or health status). ...
... An ABM is initiated by generating a set number of individuals (agents) with assigned characteristics (e.g., sex or health status). These agents are then placed in a simulated scenario based upon a set of rules to explore how they fare, and the results are analyzed for the influence of assigned characteristics on individual and group-level outcomes (Romanowska et al., 2021). ...
Article
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Introduction The role of “luck” in determining individual exposure to health insults is a critical component of the processes that shape age-at-death distributions in mortality samples but is difficult to address using traditional bioarcheological analysis of skeletal materials. The present study introduces a computer simulation approach to modeling stochasticity's contribution to the mortality schedule of a simulated cohort. Methods The present study employs an agent-based model of 15,100 individuals across a 120 year period to examine the predictive value of birth frailty on age-at-death when varying the likelihood of exposure to health insults. Results Birth frailty, when accounting for varying exposure likelihood scenarios, was found to account for 18.7% of the observed variation in individual age-at-death. Analysis stratified by exposure likelihood demonstrated that birth frailty alone explains 10.2%–12.1% of the variation observed across exposure likelihood scenarios, with the stochasticity associated with exposure to health insults (i.e., severity of health insult) and mortality likelihood driving the majority of variation observed. Conclusions Stochasticity of stressor exposure and intrinsic stressor severity are underappreciated but powerful drivers of mortality in this simulation. This study demonstrates the potential value of simulation modeling for bioarchaeological research.
... In addition to this wider study of movement, we also tested the viability of Agent-Based Modelling (ABM) as a comparative tool for understanding mobility in relation to prehistoric rock art within the landscape. Although this technique has been used successfully in archaeological research [83][84][85] there has been limited application to rock art studies. As the computer power and time required to run this approach in all our Case Study areas exceeded our resources, our pilot study focused only on the Kilmartin area. ...
... ABM is a form of computer simulation used to explore and understand the characteristics of a system, and how the simulation of actions, interactions and behaviour of artificial agents lead to patterns that shape the dynamics of that system. This approach can inform multiple theoretical perspectives ( [83], p. 247, [84], p. 7). In archaeological ABM, the agents typically represent individuals or other types of social unit, although certain studies have increased the realism of these simulations by incorporating elements of social interaction, such as knowledge exchange, exchange of goods, decision-making, and environmental change [83,85]. ...
Article
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Prehistoric rock carvings are one of Scotland’s most enigmatic and poorly understood monument types. This article discusses the pioneering approach used by Scotland’s Rock Art Project to enhance understanding of the abstract motifs through multiscalar computational analyses of a large dataset co-produced with community teams. The approach can be applied to suitable rock art datasets from other parts of the world and has international relevance for rock art reserach. Our analysis incorporates data from across Scotland in order to investigate inter-regional differences and similarities in the nature and contexts of the carvings. Innovative application of complementary analytical methods identified subtle regional variations in the character of the rock art and motif types. This variability suggest an understanding of the rock art tradition that was widely shared but locally adapted, and reflects connections and knowledge exchange between specific regions.
... Dependiendo del campo, disciplinas y experiencia académica, es posible que el lector desconozca del todo el término de «simulación social». Gran parte de lo que aquí se referirá con este término es, actualmente, más familiar a la mayoría de los investigadores en arqueología como «modelizado basado en agentes» (MBA; en inglés, agent-based modelling o ABM) (Romanowska et al., 2021), mientras «simulación social» es más extendido en otras disciplinas en ciencias sociales, sobre todo la sociología (GilbeRt y tRoitzsch, 2006). Veremos, empero, que estos términos, aunque muy relacionados, no son estrictamente sinónimos. ...
... Dado que aquí solo podemos mencionar una pequeña parte del campo, para una mayor profundización sobre el potencial de la simulación social en arqueología se remite a las muchas introducciones y contribuciones disponibles en castellano (códova, 2003;paRdo-GoRdó, 2017; Rubio-campillo, 2017) e inglés (bReiteneckeR et al., 2015;ceGielski y RoGeRs, 2016;GRaham, 2020;kowaRik et al., 2012;lake, 2014Romanowska et al., 2019;wuRzeR et al., 2015). A los futuros practicantes, se recomienda especialmente el libro de texto «Agentbased Modeling for Archaeology» (Romanowska et al., 2021), que incluye muchos ejemplos y ejercicios prácticos. ...
Article
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Vegueta. Anuario de la Facultad de Geografía e Historia 23 (1), 2023, 15-55 eISSN: 2341-1112 https://doi.org/10.51349/veg.2023.1.02 Se presenta una revisión epistemológica de la simulación social en arqueología, delimitándola como práctica, método y como rama de la arqueología. Como práctica, se posiciona la simulación social entre otros tipos de aplicaciones intensivas de tecnologías digitales en humanidades y ciencias sociales. Como método, la definimos como una forma de modelización matemática que contiene mecanismos, sobre todo sociales, y pide soluciones numéricas. Presentamos brevemente las características de la simulación social, incluyendo el papel central de la modelización basada en agentes. Finalmente, contextualizamos el lugar de la simulación social en arqueología, ofreciendo una breve revisión de ejemplos de aplicación.
... Once the model is set in motion, the interaction of the agents leads to a bottom-up process, where the emergence of a series of patterns and signals can be studied. As expressed by Romanowska et al. (2021), an Agent-Based Model contains three key elements: ...
... This has indeed been put to practice by several modelers. For example, and following Romanowska et al. (2021), ABMs have been used with non-organic agents, as varied as households, settlements, cars or even phonemes. ...
... At every step, agents secure their subsistence through local mobility (to neighboring cells) using an imperfect hill climbing algorithm (107) and resource exploitation, i.e., harvesting and then consuming resources. If an agent's resource level falls below a defined threshold (their daily metabolic needs for most strategies or a depleted infrastructure level for infrastructure), i.e., they enter into a bad year, then this triggers one of the four resilience strategies: mobility, Table 1. ...
Article
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Resilience—the ability of socio-ecological systems to withstand and recover from shocks—is a key research and policy focus. Definitions of resilience differ between disciplines, however, and the term remains inadequately operationalized. Resilience is the outcome of variable behavioral decisions, yet the process itself and the strategies behind it have rarely been addressed quantitatively. We present an agent-based model integrating four common risk management strategies, observed in past and present societies. Model outcomes under different environmental regimes, and in relation to key case studies, provide a mapping between the efficacy (success in harm prevention) and efficiency (cost of harm prevention) of different behavioral strategies. This formalization unravels the historical contingency of dynamic socio-natural processes in the context of crises. In discriminating between successful and failed risk management strategies deployed in the past—the emergent outcome of which is resilience—we are better placed to understand and to some degree predict their utility in the contemporary world.
... By studying historic artifacts and remains, archeology helps us uncover the stories of our ancestors, revealing how they lived, worked, and shaped the world we inherit. Recently, agent-based simulation (ABS) has been increasingly employed for archeological research [1,2]. ABS involves modeling an agent, which is an autonomous decision-making entity, as a fundamental component of a system. ...
Chapter
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This chapter proposes a new framework that analyzes the log data from computational simulations to integrate agent-based simulation (ABS) with conventional fieldwork-based research in archeology. Specifically, machine learning methods are employed to extract the key branch points of each result from a large and diverse set of simulation results and the log data representing the process leading to them. In this framework, the ABS results are used to develop working hypotheses for facilitating fieldwork-based research, whereas those of fieldwork are used as inputs for the simulations, thereby resulting in bidirectional links rather than unidirectional ones. In a pilot application of this framework, the log data from a simulation of the cultural transformation from the Jomon period to the Yayoi period (16,000 to 2350 cal BP) in Western Japan are analyzed.
... MCMs can also be viewed as a special type of a multi-agent system [74]. In addition, the MCMs model can be viewed as a special case of a collective [100,92,93,101], where rather than an (exact) potential game [57,13], we have a team game [54], and the precise form of the communication among the members of the collective must obey multiple constraints. ...
Preprint
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Social evolutionary theory seeks to explain increases in the scale and complexity of human societies, from origins to present. Over the course of the twentieth century, social evolutionary theory largely fell out of favor as a way of investigating human history, just as advances in complex systems science and computer science saw the emergence of powerful new conceptions of complex systems, and in particular new methods of measuring complexity. We propose that these advances in our understanding of complex systems and computer science should be brought to bear on our investigations into human history. To that end, we present a new framework for modeling how human societies co-evolve with their biotic environments, recognizing that both a society and its environment are computers. This leads us to model the dynamics of each of those two systems using the same, new kind of computational machine, which we define here. For simplicity, we construe a society as a set of interacting occupations and technologies. Similarly, under such a model, a biotic environment is a set of interacting distinct ecological and climatic processes. This provides novel ways to characterize social complexity, which we hope will cast new light on the archaeological and historical records. Our framework also provides a natural way to formalize both the energetic (thermodynamic) costs required by a society as it runs, and the ways it can extract thermodynamic resources from the environment in order to pay for those costs -- and perhaps to grow with any left-over resources.
... Over the past ten years, the growing number of pedagogical manuals presenting the principles and expectations of agent-based modelling [53][54][55][56] testifies to the strongest interest in this approach in various disciplines [57]. We would like to mention a first book more specifically intended for archaeologists [58], recently published by the Santa Fe Institute, which promotes the use of agent-based systems in the field of social sciences and complexity from the United States. ...
Article
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What impact did the Roman Climate Optimum (RCO) and the Late Antique Little Ice Age (LALIA) have on the rise and fall of the Roman Empire? Our article presents an agent-based modelling (ABM) approach developed to evaluate the impact of climate change on the profitability of vineyards, olive groves, and grain farms in Southern Gaul, which were the main source of wealth in the roman period. This ABM simulates an agroecosystem model which processes potential agricultural yield values from paleoclimatic data. The model calculates the revenues made by agricultural exploitations from the sale of crops whose annual volumes vary according to climate and market prices. The potential profits made by the different agricultural exploitations are calculated by deducting from the income the operating and transportation costs. We conclude that the warm and wet climate of the Roman period may have had an extremely beneficial effect on the profitability of wine and olive farms between the 2nd century BCE and the 3rd century CE, but a more modest effect on grain production. Subsequently, there is a significant decrease in the potential profitability of farms during the Late Antique Little Ice Age (4th-7th century CE). Comparing the results of our model with archaeological data enables us to discuss the impact of these climatic fluctuations on the agricultural and economic growth, and then their subsequent recession in Southern Gaul from the beginning to the end of antiquity.
... All models are abstractions of the real world and are by definition limited in scope, realism, and detail (Box and Draper, 1987), but deductive models are flexible and are preferred for the initial exploration of the capacity for emergence within a general problem domain (Robinson et al., 2007;Rounsevell et al., 2012;Railsback and Grimm, 2019). Specificity and complexity are added to the model as required by our understanding of the behavior, or as the model problem domain evolves, which is the approach that we have taken here (Railsback and Grimm, 2019;Romanowska et al., 2021). We think that these methods may allow us to take lessons from past extinction dynamics and apply them to present SES by identifying extinction thresholds and the ways in which such systems move towards or away from them. ...
Article
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The role of human hunting behavior versus climate change in the mass extinction of megafauna during the Late Quaternary is much debated. To move beyond monocausal arguments, we treat human–megafauna–environment relationships as social–ecological systems from a complex adaptive systems perspective, to create an agent-based model that tests how human hunting may interact with environmental stress and animal life history to affect the probability of extinction. Using the extinction of Syncerus antiquus in South Africa at 12–10 ka as a loose inspirational case study, we parameterized a set of experiments to identify cross-feedbacks among environmental dynamics, prey life history, and human hunting pressure that affect extinction probability in a non-linear way. An important anthropogenic boundary condition emerges when hunting strategies interrupt prey animal breeding cycles. This effect is amplified in patchy, highly seasonal environments to increase the chances of extinction. This modeling approach to human behavior and biodiversity loss helps us understand how these types of cross-feedback effects and boundary conditions emerge as system components interact and change. We argue that this approach can help translate archaeological data and insight about past extinction for use in understanding and combating the current mass extinction crisis.
... This has led historical scientists to be branded as "methodological omnivores" (Currie, 2018). Computational modelling is one of many methodological branches that archaeologists have turned to in pursuit of better understanding the past (Gavin, 2014;Kohler & Gumerman, 2000;Romanowska et al., 2019Romanowska et al., , 2021Wurzer et al., 2015). In a seminal paper, Weaver (1948) distinguished three phases of science, corresponding each to a specific type of system it was ideally poised to deal with: (1) simple systems such as pendulums and machine mechanics; (2) disorganized complex systems such as gases and crowds; and (3) organized complex systems such as cities, economies and ecosystems. ...
Chapter
All human societies need energy and resources in order to sustain themselves. Individual decisions on how to meet these needs necessarily impact on the possibilities of other nearby actors to meet their own. The range of exploitation possibilities thus becomes limited by the proximity to others in tandem with the (re)generative capacity of the local landscape. In this paper, we present results from SAGAscape, an agent-based model of resource exploitation and subsistence in the area of Sagalassos (southwest Turkey) from Middle Iron Age to Early Hellenistic times (900–200 BC). The model simulates the harvesting of food, wood and clay by individually-optimizing households, seeking to fulfil the collective needs of their communities. Our results show how the behavior of these households leads to distinct spatial patterns in land use and how sustainability depends simultaneously on a settlement’s environment as it does on its neighbors. The use of known, periodized sites generates new hypotheses with regards to observed settlement patterns as well as the nature of property regimes in these periods. Through the continued development of SAGAscape, we intend to bring the significant potential of agent-based modelling for archaeology to further fruition.KeywordsAnatoliaResource exploitationIron ageHellenisticAgent-based modelling
... When each agent spends more time on the landscape (high μ value), agents create more blanks, and scavenge, discard, and retouch more artifacts on average (Fig 8). This effect may be in part due a burn-in effect [61] since one timestep is used to place a new agent into the landscape and agents are initialized with no objects. Higher μ values result in longer agent activity periods, therefore reducing the number of timesteps in a model run used to initialize a new agent. ...
Article
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Recycling behaviors are becoming increasingly recognized as important parts of the production and use of stone tools in the Paleolithic. Yet, there are still no well-defined expectations for how recycling affects the appearance of the archaeological record across landscapes. Using an agent-based model of recycling in surface contexts, this study looks how the archaeological record changes under different conditions of recycling frequency, occupational intensity, mobility, and artifact selection. The simulations also show that while an increased number of recycled artifacts across a landscape does indicate the occurrence of more scavenging and recycling behaviors generally, the location of large numbers of recycled artifacts is not necessarily where the scavenging itself happened. This is particularly true when mobility patterns mean each foraging group spend more time moving around the landscape. The results of the simulations also demonstrate that recycled artifacts are typically those that have been exposed longer in surface contexts, confirming hypothesized relationships between recycling and exposure. In addition to these findings, the recycling simulation shows how archaeological record formation due to recycling behaviors is affected by mobility strategies and selection preferences. While only a simplified model of recycling behaviors, the results of this simulations give us insight into how to better interpret recycling behaviors from the archaeological record, specifically demonstrating the importance of contextualizing the occurrence of recycled artifacts on a wider landscape-level scale.
... Other areas of improvement include the sometimes inappropriate use of modern landform configurations in GISbased approaches, despite the increasing availability paleogeographic models (Borreggine et al., 2022). Another problem, highlighted elsewhere, is that GIS-based models are static whereas the complex systems being modelled are dynamic -although, once again, new methods are being developed to counter this challenge (Romanowska et al., 2021). ...
... At the intersection of social network analysis and social simulation, researchers have begun to use agent-based models to examine the role of generative behavioral mechanisms on social network formation, such as advice and friendship networks, by exploring various underlying mechanisms and fitting models to empirical data [60,66]. In more qualitative research areas, following the famous application on the Anasazi in the Long House Valley in Arizona between 800 and 1350 [2], archaeologists are now using rich, context-specific agent-based models to test the effect of social structures on past trajectories of extinct populations in various geographical regions (e.g., see [56]). Re-running past historical periods with computer simulations requires integrating data and insights from various disciplines so that counter factual 'as if' tests on historical trajectories can be performed [9]. ...
Chapter
This chapter introduces the proceedings of the Social Simulation Conference 2022 by providing a brief overview of the impact of social simulation in various research areas. By focusing on the key role of agent-based modeling, we argue that social simulation has a unique position in the wider data science area. This is because it can enrich the predominantly inductive, data-driven, pattern oriented approach of computational social science with deductive, hypothesis-driven, explanatory, mechanism-detection models. Furthermore, social simulation can also work in areas and for contexts where data is not available, experiments cannot be performed or in which scenario exploration is paramount. We would also like to focus on areas and aspects where methodological improvement and cross-methodological integration are required to enhance the potential of social simulation in various communities. In the final section, we introduce the structure and sections of the proceedings.
... Linde and Robra [21] have also done experimental archaeological recording in Dwarf Fortress. Though somewhat tangential to archaeogaming, Agent Based Modelling has been used extensively by archaeologists as a way of extrapolating from archaeological data [14,34]. ...
Preprint
Procedural content generation has been applied to many domains, especially level design, but the narrative affordances of generated game environments are comparatively understudied. In this paper we present our first attempt to study these effects through the lens of what we call a generative archaeology game that prompts the player to archaeologically interpret the generated content of the game world. We report on a survey that gathered qualitative and quantitative data on the experiences of 187 participants playing the game Nothing Beside Remains. We provide some preliminary analysis of our intentional attempt to prompt player interpretation, and the unintentional effects of a glitch on the player experience of the game.
... Lake's comment (2000) was accurate that modelling has not been at the forefront of mainstream archaeology during these past years; however, it has found a niche in archaeology, and remains a relatively active research subject as exemplified by recent studies, e.g. Brantingham (2003), Barton et al. (2011Barton et al. ( , 2012, Kohler et al. (2012Kohler et al. ( , 2018, Rubio Campillo et al. (2012), Altaweel (2014), Romanowska et al. (2021). ...
... By their nature, digital spaces are affected as soon as a human agent enters them. Care must be taken to acknowledge and observe those effects on human and nonhuman agents prior to moving ahead with any fieldwork or experimentation (Graham 2017(Graham , 2020Romanowska et al. 2021). Some digital environments can be fragile, and interactions within them can be destructive unintentionally. ...
Article
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In the last decade, archaeologists have been using human-occupied interactive digital built environments to investigate human agency, settlement, and behavior. To document this evidence, we provide here one method of conducting drone-based photogrammetry and GIS mapping from within these digital spaces based on well-established methods conducted in physical landscapes. Mapping is an integral part of archaeology in the natural world, but it has largely eluded researchers in these new, populated digital landscapes. We hope that our proposed method helps to resolve this issue. We argue that employing archaeological methods in digital environments provides a successful methodological framework to investigate human agency in digital spaces for anthropological purposes and has the potential for extrapolating data from human-digital landscape interactions and applying them to their natural analogues.
... The elucidation of spatiotemporal patterns regarding prehistoric maritime mobility has attracted global archaeological attention over the past 20 years within the context of island and maritime archaeology (especially in the Eastern Mediterranean), as they provide insights in understanding colonization pathways [1,2], maritime technological capacity [3,4] and social behavior of early colonists [5]. To that end, computer simulation models for seaborne movement were developed over the years, closely related to agentbased models [6], although not always explicitly stated as such. In such models, multiple virtual vessels embark from coastal locations and interact (in a stochastic or deterministic way) with winds, currents and (possibly) waves according to their postulated structural characteristics as well as their navigation skills and trip motivation. ...
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Seaborne movement underpins frontier research in prehistoric archaeology, including water-crossings in the context of human dispersals, and island colonisation. Yet, it also controls the degree of interaction between locations, which in turn is essential for investigating the properties of maritime networks. The onset of the Holocene (circa 12,000 years ago) is a critical period for understanding the origins of early visitors/inhabitants to the island of Cyprus in the Eastern Mediterranean in connection with the spread of Neolithic cultures in the region. The research undertaken in this work exemplifies the synergies between archaeology, physical sciences and geomatics, towards providing novel insights on the feasibility of drift-induced seaborne movement and the corresponding trip duration between Cyprus and coastal regions on the surrounding mainland. The overarching objective is to support archaeological inquiry regarding the possible origins of these visitors/inhabitants—Anatolia and/or the Levant being two suggested origins.
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Archaeological research in northern Sweden has customarily proposed models based on assumed migration patterns to portray resource utilization of prehistoric hunter-gatherers. An average hunting household needs about 500km2 for its subsistence. This assumption, as well as the temporal and spatial distribution of animal resources available for hunting households in the interior of Northern Sweden, is investigated using Agent Based Modelling (ABM) with explicitly identified factors and conditions. ABM simulations were run in order to analyse the relationships between hunters, moose (Alces alces), predators, landscapes and how human migration patterns could be adjusted in order to coincide with moose migrations. The results suggest that wolves and human hunters could coexist if the landscape had a moose density of 0.6 moose/km2 or more and if each hunting household possessed territories of 400–500km2. In accordance with the model’s parameters, the simulation identifies those factors that are particularly sensitive to change and those factors that are necessary in order to maintain an ecological balance between hunters and their prey.
Article
For a long time, lithic procurement strategies have been used as an indicator of mobility abilities and material preferences of various hunter-gatherer groups across time. Different procurement patterns between the Middle and Upper Palaeolithic in Europe have led to interpretations of species differences between Homo neanderthalensis and Homo sapiens , and diverse influences of the environment on the populations. With the use of hypotheses on local or long-distance lithic procurement, agent-based models can function as a neutral and quantitative test of procurement choices. By statistically testing hypotheses made from ethnographic and archaeological studies, the material of four Middle Palaeolithic sites in the Middle Rhine area, Western Germany, set the frame for analysing procurement choices of the Neanderthals in their environmental setting. From the analyses of the agent-based models, it is visible that it is the availability of raw material resources that influences the procurement of the hunter-gatherer agent. By reflecting this result in the local environment and ecological options, it is argued that the advantages of local procurement succeeded the ones of long-distanced procurements for the Neanderthals. Thereby the study provides an example of the beneficial union of qualitative and quantitative methodologies in archaeological research, and how the science of the past can improve by adding computational methods of the present.
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Since the early 1960s, obsidian provenance has been based on the geochemical analysis of volcanic glass sources and interpretation of the results obtained for archaeological purposes.
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El objetivo de este capítulo es construir las bases teóricas para un modelo de movilidad urbana feminista con enfoque interseccional, como un ejercicio de abstracción con la técnica de Modelado Basado en Agentes (MBA). Para ello, se toma como base la propuesta de movilidad feminista de Col-lectiu Punt 6 (2021) y la política de movilidad de Cresswell (2010), como metodología se sigue el protocolo ODD y, finalmente, se llega a una propuesta de conceptualización para el desarrollo Modelo de Movilidad Peatonal con Enfoque Interseccional (MMPEI).
Book
Ciudad y sustentabilidad: movilidades urbanas es una obra colectiva que, desde distintos enfoques y aproximaciones metodológicas, busca contribuir a la reflexión sobre las movilidades en las ciudades, a partir del análisis de distintos aspectos relacionados con la inclusión o exclusión del espacio urbano de diversos grupos sociales, como mujeres, personas con problemas de movimiento, jóvenes, “tecolines”, migrantes y turistas, en sus desplazamientos cotidianos entre lugares y en los lugares.
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Background Simulations, ludic or otherwise, have so far struggled to gain a foothold in mainstream historiography. Some authors suggest there may be fundamental incompatibilities between history and the language of simulations and scholarly games. Others believe that designing, employing, and validating historical simulations may be simply too costly and/or labor-intensive to justify their widespread adoption. Intervention This paper intends to identify points of friction between historiography and simulation-based research and suggest practical solutions to these issues. Methods My discussion is based on the description and analysis of a case study, the ThomondSim/ The Triumphs of Turlough research project. The initiative consisted of the development and application of an agent-based computational model (ABM) and a scholarly board game to investigate the possible associations between economic, environmental, and military hazards in 13th and 14th centuries Ireland. Results and Discussion Ensuring the simulations matched historical evidence to a standard deemed acceptable by the historiographical community limited their phase space, compromising their capacity to explore emergent phenomena. The intricacy of the underlying conceptual model suited the ABM better than the board game, which struggled to reconcile complexity with good game design practices. The board game, however, proved to be an effective validating tool for the ABM. Limitations and Suggestions for Further Research The project espoused an overt simulation- and game-centric approach, paying little attention to unguided play. Recent literature suggests that fostering, rather than hindering, playful exploration could address some of the pitfalls identified by this project. Conclusion Play could be a means of reconciliation between simulational, ludic, and historiographical practices. However, to ensure that projects adhere to epistemic standards, it is recommended that a methodology is developed to integrate it into research in ways that can be tested and evaluated.
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Rivers are often seen to have played an important role for Palaeolithic hunter-gatherers as landmarks and resource location. While the former view regards rivers as passive guidelines or obstacles, the latter reduces them to their economic value. Both views, therefore, look at generic properties, equally valid for all streams and their sections and partly overlook the interaction between humans and specific rivers within the landscape. In this article, we contribute to the discussion by looking explicitly at an historically contingent and specific case of interaction between humans and a particular section of an individual river, i.e., the Rhine in the Neuwied Basin. Using an agent-based model, we aim at identifying differences in water-oriented land use decisions between the Late Upper and Late Palaeolithic occupations of the region. We observe a clear shift from a dominant focal role of the Rhine during the former to a less important spatial entity during the latter period and conclude that these differences are as much an expression of a changed perception of the Rhine as they are a result of environmental change and the transition from a pioneering to a stationary settlement phase and that indeed both aspects are inextricably intertwined.
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Sustainability outcomes are influenced by the laws and configurations of natural and engineered systems as well as activities in socio-economic systems. An important subset of human activity is the creation and implementation of institutions, formal and informal rules shaping a wide range of human behavior. Understanding these rules and codifying them in computational models can provide important missing insights into why systems function the way they do (static) as well as the pace and structure of transitions required to improve sustainability (dynamic). Here, we conduct a comparative synthesis of three modeling approaches— integrated assessment modeling, engineering–economic optimization, and agent-based modeling—with underexplored potential to represent institutions. We first perform modeling experiments on climate mitigation systems that represent specific aspects of heterogeneous institutions, including formal policies and institutional coordination, and informal attitudes and norms. We find measurable but uneven aggregate impacts, while more politically meaningful distributional impacts are large across various actors. Our results show that omitting institutions can influence the costs of climate mitigation and miss opportunities to leverage institutional forces to speed up emissions reduction. These experiments allow us to explore the capacity of each modeling approach to represent insitutions and to lay out a vision for the next frontier of endogenizing institutional change in sustainability science models. To bridge the gap between modeling, theories, and empirical evidence on social institutions, this research agenda calls for joint efforts between sustainability modelers who wish to explore and incorporate institutional detail, and social scientists studying the socio-political and economic foundations for sustainability transitions.
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Bringing together a wide array of modern scientific techniques and interdisciplinary approaches, this book provides an accessible guide to the methods that form the current bedrock of research into Roman, and more broadly ancient, wine. Chapters are arranged into thematic sections, covering biomolecular archaeology and chemical analysis, archaeobotany and palynology, vineyard and landscape archaeology and computational and experimental archaeology. These include discussions of some of the most recent techniques, such as ancient DNA and organic residue analyses, geophysical prospection, multispectral imaging and spatial and climatic modelling. While most of the content is of direct relevance to the Roman Mediterranean, the assortment of detailed case studies, methodological outlines and broader ‘state of the field’ reflections is of equal use to researchers working across disparate disciplines, geographies, and chronologies. The study of ancient Roman wine has been dominated until recently by traditional archaeological analyses focused upon production facilities and ceramic evidence related to transport. While such architecture and artefact-focussed approaches provide a fundamental foundation for our understanding of this topic, they fail to provide the requisite nuance to answer other questions regarding grape cultivation and wine production, consumption, use and trade. As the first compendium of its kind, this book supports the embedding of modern scientific and experimental techniques into archaeological fieldwork, research and laboratory analysis, pushing the boundaries of what questions can be explored, and serving as a launching point for future avenues of interdisciplinary research. This volume presents an array of cutting-edge scientific and archaeological methodologies used in the study of vine-growing and winemaking in the Graeco-Roman Mediterranean. Recent work on this subject tends to be dominated by traditional archaeological analyses of press facilities and, above all, ceramic evidence. These approaches lack the nuance to answer several vital questions about Greek and Roman grapevine cultivation and wine production, consumption, use and trade. In response, modern scientific techniques are increasingly filling these gaps in both fieldwork and laboratory contexts. By bringing together a wide range of disciplinary approaches in one location, this book provides an accessible guide to the scientific methodologies that form the new bedrock of current research on ancient wine. Arranged into thematic sections covering biomolecular archaeology and chemical analysis, archaeobotany and palynology, vineyard and landscape archaeology, and computational modelling and experimental archaeology, its detailed exemplary case studies and ‘state of the field’ chapters can be immediately utilized by researchers working across disparate fields, chronologies and research contexts as reliable points of reference. As the first compendium of its kind, it aims to foster interconnection of modern scientific technologies with archaeological fieldwork and analysis, pushing the boundaries of what questions can be explored and serving as a foundation for future avenues of research into ancient wine production.
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Agent-based modelling allows researchers to build artificial pastoral systems that are spatially explicit and allow for the examination of complex interactions between households, herds, and rangelands over long time periods. However, agent-based modelling also necessarily reduces the complexity of the pastoral systems. The question that we examine in this paper is how researchers model pastoral systems and what artificial pastoral systems they create. To answer that question, we systematically reviewed 35 agent-based modelling studies of pastoral systems. We examined how the studies describe the focal pastoral system, how the focal system is represented in a conceptual model, implemented in computer code, and how it emerges as an artificial pastoral system from the simulations. Our review indicates that most models are built by interdisciplinary teams, integrated into empirical studies of pastoral systems, and use a specific pastoral system as its focal system. The research problems explored in the models range from resource management, wealth dynamics, herd demography, sustainability, adaptation, mobility, and conflict. The artificial pastoral systems that emerge from these agent-based modelling studies mostly confirm current theoretical understandings that are based on empirical studies of pastoral systems. There are a few emergent patterns that have not been validated extensively in empirical studies. We conclude with a discussion of the theoretical, methodological, and practical implications of using agent-based models to create artificial pastoral systems.
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Throughout the history of archaeology, researchers have evaluated human societies in terms of systems and systems interactions. Complex systems theory (CST), which emerged in the 1980s, is a framework that can explain the emergence of new organizational forms. Its ability to capture nonlinear dynamics and account for human agency make CST a powerful analytical framework for archaeologists. While CST has been present within archaeology for several decades (most notably through the use of concepts like resilience and complex adaptive systems), recent increases in the use of methods like network analysis and agent-based modeling are accelerating the use of CST among archaeologists. This article reviews complex systems approaches and their relationship to past and present archaeological thought. In particular, CST has made important advancements in studies of adaptation and resilience, cycles of social and political development, and the identification of scaling relationships in human systems. Ultimately, CST helps reveal important patterns and relationships that are pivotal for understanding human systems and the relationships that define different societies.
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Prehistoric rock carvings are one of Scotland’s most enigmatic and poorly understood monument types. This article discusses the pioneering approach used by Scotland’s Rock Art Project to enhance understanding of the abstract motifs through multiscalar computational analyses of a large dataset co-produced with community teams. The analysis incorporates data from across the country in order to investigate inter-regional differences and similarities in the nature and contexts of the carvings. Innovative application of complementary analytical methods identified subtle regional variations in the character of the rock art and motif types. This variability suggest an understanding of the rock art tradition that was widely shared but locally adapted, and reflects connections and knowledge exchange between specific regions.
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Este artículo discute las consideraciones teóricas, metodológicas y de instrumentación con las que es posible y necesario trabajar para auxiliar en la detección de restos humanos en contextos sumergidos de una manera científica, sistemática, y reproducible. Esta labor es también copartícipe del propósito de hacer de la arqueología una herramienta para ayudar a cerrar procesos profundamente dolorosos entre las familias que han sufrido pérdidas en el grave contexto de desapariciones forzadas en el México actual. Se consideran como parte del análisis los siguientes elementos clave: 1) la necesidad de un desarrollo explícitamente teórico en arqueología que incorpora estrategias para la resolución de preguntas, tal como es el caso de la arqueología procesual; 2) el análisis de las alteraciones tafonómicas que afectarán a un cuerpo humano y que se presentan en el escenario de un contexto sumergido, y, 3) el desarrollo de una metodología de prospección que incorpora tecnologías de punta de lanza en la arqueología marítima contemporánea, con énfasis en instrumentación de posicionamiento, geofísica marina, fotogrametría, robótica y buceo técnico y científico.
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Between 1276 and 1318, English magnates unsuccessfully attempted to establish a lordship in the Irish kingdom of Thomond, southwestern Ireland, by exploiting a dynastic feud dividing the then-ruling lineage, the Uí Bhriain. The conflict coincided with a series of extreme events that beset western Europe in the late 13th and early 14th centuries, such as the beginning of the Little Ice Age and the Great European Famine of 1315–1322. The goal of this work was to evaluate to the extent to which economic degradation at the turn of the 14th century affected the outcome of the war. The hypothesis that such degradation affected the war’s outcome was tested using agent-based modeling, which involved the virtual reconstruction of Late Medieval Thomond to study past conditions by proxy. This article describes the historical research carried out to elaborate the conceptual model, the implementation of the model as a computer simulation, and the experiments carried out to virtually explore the Uí Bhriain Civil War. A quantitative analysis of the experimental results revealed some correlation between late 13th century economic degradation and the fortunes of belligerent factions in the wars of 1276–1318, although the effect was not sufficiently strong to have been a crucial factor in the outcome of the conflict.
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If we are to analyze the diet of past foragers, we need to understand how humans make hunting choices. Originating from behavioral ecology, several models issued from the Optimal Foraging Theory offer important insights about human diets. Since the “Broad Spectrum Revolution” hypothesis proposed by Flannery in 1969, the Diet Breadth Model (DBM) has been used in Europe and Western Asia to explain the relevance of small-game hunting in the past. In particular, archaeological evidence indicates that rabbit hunting became more prevalent during the Upper Palaeolithic in the Iberian Peninsula. Based on the DBM, it has been suggested that warren hunting through the use of nets may explain the introduction of rabbits in the optimal diet of humans and thus justify the exploitation of rabbits observed in the fossil record. In this chapter, we discuss the benefits and limits of the DBM as a tool for understanding human prey selection. We argue that combining the theoretical strengths of the DBM with the dynamism of an Agent-Based Model (ABM) is a robust method that offers insights about the exploitation of rabbits during the Last Glacial Maximum in Iberia. Our results show that the predictions made by the DBM are confirmed by the ABM, namely the exploitation of prey types that are predicted to belong to the optimal diet by the DBM. Finally, we suggest that hunting choices made by humans might be driven by other factors than the ones entailed in our DBM-grounded ABM, i.e., optimalising energy gains. Social factors in which big game hunting may take place (e.g., social status of men) and the broader context in which communal warren-based harvesting occurs, such as the organisation of labour among members of a band, need to be considered in future research.
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The paper proposes a new methodological approach aimed at developing simulation models of system dynamics and agent-based modeling in case an enterprise introduces an innovative patented technology in new markets. This task requires development of new business models, strategies, and communication processes. The operating models for solving these problems are implemented in the AnyLogic simulation system
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Understanding how resource characteristics influence variability in social and material inequality among foraging populations is a prominent area of research. However, obtaining cross-comparative data from which to evaluate theoretically informed resource characteristic factors has proved difficult, particularly for investigating interactions of characteristics. Therefore, we develop an agent-based model to evaluate how five key characteristics of primary resources (predictability, heterogeneity, abundance, economy of scale and monopolizability) structure pay-offs and explore how they interact to favour both egalitarianism and inequality. Using iterated simulations from 243 unique combinations of resource characteristics analysed with an ensemble machine-learning approach, we find the predictability and heterogeneity of key resources have the greatest influence on selection for egalitarian and nonegalitarian outcomes. These results help explain the prevalence of egalitarianism among foraging populations, as many groups probably relied on resources that were both relatively less predictable and more homogeneously distributed. The results also help explain rare forager inequality, as comparison with ethnographic and archaeological examples suggests the instances of inequality track strongly with reliance on resources that were predictable and heterogeneously distributed. Future work quantifying comparable measures of these two variables, in particular, may be able to identify additional instances of forager inequality. This article is part of the theme issue ‘Evolutionary ecology of inequality’.
Article
Background: There is a wide variety of potential sources from which insight into the antiquities trade could be culled, from newspaper articles to auction catalogues, to court dockets, to personal archives, if it could all be systematically examined. We explore the use of a large language model, GPT-3, to semi-automate the creation of a knowledge graph of a body of scholarship concerning the antiquities trade. Methods: We give GPT-3 a prompt guiding it to identify knowledge statements around the trade. Given GPT-3’s understanding of the statistical properties of language, our prompt teaches GPT-3 to append text to each article we feed it where the appended text summarizes the knowledge in the article. The summary is in the form of a list of subject, predicate, and object relationships, representing a knowledge graph. Previously we created such lists by manually annotating the source articles. We compare the result of this automatic process with a knowledge graph created from the same sources via hand. When such knowledge graphs are projected into a multi-dimensional embedding model using a neural network (via the Ampligraph open-source Python library), the relative positioning of entities implies the probability of a connection; the direction of the positioning implies the kind of connection. Thus, we can interrogate the embedding model to discover new probable relationships. The results can generate new insight about the antiquity trade, suggesting possible avenues of research. Results: We find that our semi-automatic approach to generating the knowledge graph in the first place produces comparable results to our hand-made version, but at an enormous savings of time and a possible expansion of the amount of materials we can consider. Conclusions: These results have implications for working with other kinds of archaeological knowledge in grey literature, reports, articles, and other venues via computational means.
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Archaeologists have long considered climate change a primary mechanism behind human behavioral adaptations. The Lesotho highlands’ Afromontane and climatically extreme environments offer a unique opportunity to examine proposed correlations between topography, climate, and human behavior. Previous studies suggest that warmer temperatures allowed humans to expand their diet breadth and foraging range, whereas colder temperatures restricted humans to resources in riverine corridors. These studies used faunal and floral change as proxies to track changes in forager mobility but did not consider how differential access to stone resources affected human behaviors. To account for this gap, we conducted a survey for knappable rocks around the Sehonghong rock shelter in eastern Lesotho, recording the materials present and their size and shape in the modern environment. We compared the survey results to later Pleistocene (~ 22–11 ka cal. BP) lithic assemblages at Sehonghong to better understand whether archaeological patterns match modern knappable rock availability. Contrary to previous hypotheses, we find that past peoples at Sehonghong were not limited to exclusively riverine resources during colder conditions. We then used flake-to-core and noncortical-to-cortical flake ratios to track changes in mobility and knappable rock procurement patterns. The ratios remain constant up until the Late Glacial, ca. 14 ka cal. BP, when we see an increase in both flake-to-core and noncortical-to-cortical ratios, suggesting increased movement of stone out of Sehonghong. These conclusions show that resource procurement and mobility patterns are not solely dependent on climate change but may be driven by more complicated causal mechanisms such as increased interaction and the formation of social networks across the Lesotho highlands and beyond.
Book
This volume contains a collection of research aimed towards understanding prehistoric subsistence change with the use of new computational modeling techniques. There is a sort of poetic irony when using humanity’s newest technology to study early human history. The distance between past and future almost appears highlighted when using a tablet to record an archaeological site or a differential equation to understand hunter-gatherer mobility. Yet, archaeology has always been at the forefront of modern scientific techniques and tools as a means to understand the past. Today, archaeologists may have one hand on a projectile point while the other commands a high-performance computing cluster.
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The Cambridge Manual to Archaeological Network Science provides the first comprehensive guide to a field of research that has firmly established itself within archaeological practice in recent years. Network science methods are commonly used to explore big archaeological datasets and are essential for the formal study of past relational phenomena: social networks, transport systems, communication, and exchange. The volume offers a step-by-step description of network science methods and explores its theoretical foundations and applications in archaeological research, which are elaborately illustrated with archaeological examples. It also covers a vast range of network science techniques that can enhance archaeological research, including network data collection and management, exploratory network analysis, sampling issues and sensitivity analysis, spatial networks, and network visualisation. An essential reference handbook for both beginning and experienced archaeological network researchers, the volume includes boxes with definitions, boxed examples, exercises, and online supplementary learning and teaching materials.
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The perceptibility of a prehistoric monument (the property of being perceptible from its surrounding landscape) can be quite difficult to analyse by means of traditional static models. Such difficulty lies in the fact that perceptibility depends upon many other factors beyond simple topographical position, such as size, colour, contrast with the surroundings or even the specific circumstances of the audience, many such circumstances being of an immaterial nature. In this paper, we explore the potential use of Agent-Based Modelling for the analysis of archaeological perceptibility.
Article
A central question in the evolution of human language is how it emerged. Based on recent research across disciplines, we identified three processes proposed as potential driving factors behind the evolution of ‘modern’ language phenotype: i) a reduction in reactive aggression entailing a boost in prosociality and cooperation, ii) a change in early brain growth trajectory that impacted structures like the cerebellum and striatum, and thus likely impacted the (procedural) memory circuits these regions support, and iii) a demographic expansion of H. sapiens during the Middle Pleistocene. While extensively researched on their own, the interaction between these three processes has yet to be investigated systematically. We develop an abstract agent-based model to interrogate the relationship between these three factors and how they influence transmission of information within a population, which we take to be the essence of language. The model abstracts linguistic capacity to an ‘array of skills’ and investigates under what conditions the number of skills increases. The results demonstrate that there is an optimal degree of cooperation and memory capacity at which the amount of transmitted information is the highest. Our model also shows that separate linguistic communities arise under circumstances where individuals have high levels of memory capacity and there is at least a certain degree of non-cooperation. In contrast, we find no significant direct effects for population size in the process of linguistic community formation. Taken together, these results highlight the explanatory benefits of combining insights from cognitive science, archaeology, and computational modelling.
Article
Analyzing the spatial and temporal properties of information flow with a multi-century perspective could illuminate the sustainability of human resource-use strategies. This paper uses historical and archaeological datasets to assess how spatial, temporal, cognitive, and cultural limitations impact the generation and flow of information about ecosystems within past societies, and thus lead to tradeoffs in sustainable practices. While it is well understood that conflicting priorities can inhibit successful outcomes, case studies from Eastern Polynesia, the North Atlantic, and the American Southwest suggest that imperfect information can also be a major impediment to sustainability. We formally develop a conceptual model of Environmental Information Flow and Perception (EnIFPe) to examine the scale of information flow to a society and the quality of the information needed to promote sustainable coupled natural-human systems. In our case studies, we assess key aspects of information flow by focusing on food web relationships and nutrient flows in socio-ecological systems, as well as the life cycles, population dynamics, and seasonal rhythms of organisms, the patterns and timing of species’ migration, and the trajectories of human-induced environmental change. We argue that the spatial and temporal dimensions of human environments shape society’s ability to wield information, while acknowledging that varied cultural factors also focus a society’s ability to act on such information. Our analyses demonstrate the analytical importance of completed experiments from the past, and their utility for contemporary debates concerning managing imperfect information and addressing conflicting priorities in modern environmental management and resource use.
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Exchange networks created by Neolithic pastoral transhumance have been central to explaining the distant transport of obsidian since chemical analysis was first used to attribute Near Eastern artifacts to their volcanic origins in the 1960s. Since then, critical reassessments of floral, faunal, and chronological data have upended long-held interpretations regarding the emergence of food production and have demonstrated that far-traveled, nomadic pastoralists were more myth than reality, at least during the Neolithic. Despite debates regarding their proposed conveyance mechanisms, obsidian artifacts' transport has received relatively little attention compared with zooarchaeologi-cal and archaeobotanical lines of investigation. The rise of nondestructive and portable instruments permits entire obsidian assemblages to be traced to their sources, renewing their significance in elucidating connections among early pastoral and agricultural communities. Here we share our findings about the obsidian artifacts excavated from the sites of Ali Kosh and Chagha Sefid in the southern Zagros. In the 1960s and 1970s, 28 obsidian artifacts from the sites were destructively tested, and the remainder were sorted by color. Our results emphasize a dynamic, accelerating connectivity among the Early and Late Neolithic communities. Here we propose and support an alternative model for obsidian distribution among more settled communities. In brief, diversity in the obsidian assemblage accelerated diachronically, an invisible trend in the earlier studies. Our model of increasing population densities is supported by archaeological data and computational simulations, offering insights regarding the Neolithic Demographic Transition in the Zagros, an equivalent of which is commonly thought to have occurred around the world.
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