Exchange Network Topologies and Agent-Based Modeling: Economies of the Sedentary-Period Hohokam

2016 ◽  
Vol 81 (4) ◽  
pp. 623-644 ◽  
Author(s):  
Joshua Watts ◽  
Alanna Ossa
Keyword(s):  
Regional Scale ◽  
Simulated Data ◽  
Policy Implications ◽  
Exchange Networks ◽  
Agent Based ◽  
Phoenix Basin ◽  
Network Topologies ◽  
Nascent Markets ◽  
Exchange Network ◽  
The Phoenix

The origins and evolution of market-based economies remain poorly understood in part because the data from nascent markets are scarce and methods available to archaeologists are underdeveloped. Studying how markets evolved is vital for understanding the origins of a process that dominates modern economies around the world and has significant policy implications. We show how refining abstract models of exchange networks with household-scale distributional analyses and regional-scale computational agent-based models (ABMs) can lead to new understandings about the organization of a prehistoric economy. The Sedentary-period Hohokam of central Arizona—particularly for the middle Sacaton phase (A.D. 1020–1100)—have been identified as a middle-range society that traded pottery in a market-based economy, but the structure of their exchange networks is not well understood. We analyzed ceramic data from recent archaeological excavations at two sites in the Phoenix Basin using new network-inspired distributional approaches to evaluate exchange systems. Initial results were then assessed using simulated data generated by an ABM of Hohokam exchange networks. Final results indicated that the best-fitting ABM model configurations were those consistent with openly accessed market-based exchange and contributed new insights into the influence of natural landscape barriers such as the Salt River on exchange in the Phoenix Basin.

scholarly journals Simulating Spatio-Temporal Patterns of Bicycle Flows with an Agent-Based Model

2021 ◽  
Vol 10 (2) ◽  
pp. 88
Author(s):  
Dana Kaziyeva ◽  
Martin Loidl ◽  
Gudrun Wallentin
Keyword(s):  
Regional Scale ◽  
Evidence Base ◽  
Wide Field ◽  
Traffic Patterns ◽  
Agent Based Model ◽  
Validation Data ◽  
Agent Based ◽  
Mobility Behavior ◽  
Spatio Temporal ◽  
Models Validation

Transport planning strategies regard cycling promotion as a suitable means for tackling problems connected with motorized traffic such as limited space, congestion, and pollution. However, the evidence base for optimizing cycling promotion is weak in most cases, and information on bicycle patterns at a sufficient resolution is largely lacking. In this paper, we propose agent-based modeling to simulate bicycle traffic flows at a regional scale level for an entire day. The feasibility of the model is demonstrated in a use case in the Salzburg region, Austria. The simulation results in distinct spatio-temporal bicycle traffic patterns at high spatial (road segments) and temporal (minute) resolution. Scenario analysis positively assesses the model’s level of complexity, where the demographically parametrized behavior of cyclists outperforms stochastic null models. Validation with reference data from three sources shows a high correlation between simulated and observed bicycle traffic, where the predictive power is primarily related to the quality of the input and validation data. In conclusion, the implemented agent-based model successfully simulates bicycle patterns of 186,000 inhabitants within a reasonable time. This spatially explicit approach of modeling individual mobility behavior opens new opportunities for evidence-based planning and decision making in the wide field of cycling promotion

scholarly journals A Novel Multi-Agent Model for Robustness with Component Failure and Malware Propagation in Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4873
Author(s):  
Biao Xu ◽  
Minyan Lu ◽  
Hong Zhang ◽  
Cong Pan
Keyword(s):  
Wireless Sensor ◽  
Component Reliability ◽  
Agent Based ◽  
Agent Model ◽  
Cross Domain ◽  
Malware Propagation ◽  
Network Topologies ◽  
Multi Agent ◽  
Agent Characteristics ◽  
Information Domain

A wireless sensor network (WSN) is a group of sensors connected with a wireless communications infrastructure designed to monitor and send collected data to the primary server. The WSN is the cornerstone of the Internet of Things (IoT) and Industry 4.0. Robustness is an essential characteristic of WSN that enables reliable functionalities to end customers. However, existing approaches primarily focus on component reliability and malware propagation, while the robustness and security of cascading failures between the physical domain and the information domain are usually ignored. This paper proposes a cross-domain agent-based model to analyze the connectivity robustness of a system in the malware propagation process. The agent characteristics and transition rules are also described in detail. To verify the practicality of the model, three scenarios based on different network topologies are proposed. Finally, the robustness of the scenarios and the topologies are discussed.

The Impact of Raw-Material Scarcity on Ground-Stone Manufacture and Use: An Example from the Phoenix Basin Hohokam

1994 ◽  
Vol 59 (4) ◽  
pp. 680-694 ◽  
Author(s):  
Tammy Stone
Keyword(s):  
Energy Efficiency ◽  
Current Model ◽  
Classic Period ◽  
Raw Material ◽  
Ground Stone ◽  
Subsistence Economies ◽  
Phoenix Basin ◽  
Material Scarcity ◽  
The Impact ◽  
The Phoenix

Current models of ground-stone design, which relate tool morphology and size to subsistence economies, are based on assumptions of energy efficiency and processing constraints of the foodstuffs being ground. These models do not consider the impact of raw-material scarcity on ground-stone technologies. This impact is investigated here using an assemblage from the Classic-period Hohokam site of Pueblo Grande, Arizona. The current model of ground-stone design is modified to account for raw-material scarcity. Specifically, it is demonstrated that raw-material scarcity affects ground-stone manufacture, use, and discard patterns. It is argued here that studies using ground-stone assemblages to reconstruct subsistence economies must take these factors into consideration in areas where raw-material scarcity occurs.

scholarly journals Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions

2019 ◽  
Vol 23 (5) ◽  
pp. 2261-2278 ◽  
Author(s):  
Jin-Young Hyun ◽  
Shih-Yu Huang ◽  
Yi-Chen Ethan Yang ◽  
Vincent Tidwell ◽  
Jordan Macknick
Keyword(s):  
Decision Making ◽  
Risk Perception ◽  
Regional Scale ◽  
Agent Based ◽  
Natural Processes ◽  
Complex Adaptive ◽  
San Juan River ◽  
Human Decision ◽  
Decision Making Processes ◽  
Engineered Systems

Abstract. Managing water resources in a complex adaptive natural–human system is a challenge due to the difficulty of modeling human behavior under uncertain risk perception. The interaction between human-engineered systems and natural processes needs to be modeled explicitly with an approach that can quantify the influence of incomplete/ambiguous information on decision-making processes. In this study, we two-way coupled an agent-based model (ABM) with a river-routing and reservoir management model (RiverWare) to address this challenge. The human decision-making processes is described in the ABM using Bayesian inference (BI) mapping joined with a cost–loss (CL) model (BC-ABM). Incorporating BI mapping into an ABM allows an agent's psychological thinking process to be specified by a cognitive map between decisions and relevant preceding factors that could affect decision-making. A risk perception parameter is used in the BI mapping to represent an agent's belief on the preceding factors. Integration of the CL model addresses an agent's behavior caused by changing socioeconomic conditions. We use the San Juan River basin in New Mexico, USA, to demonstrate the utility of this method. The calibrated BC-ABM–RiverWare model is shown to capture the dynamics of historical irrigated area and streamflow changes. The results suggest that the proposed BC-ABM framework provides an improved representation of human decision-making processes compared to conventional rule-based ABMs that do not take risk perception into account. Future studies will focus on modifying the BI mapping to consider direct agents' interactions, up-front cost of agent's decision, and upscaling the watershed ABM to the regional scale.

Robustness, institutions, and large-scale change in social-ecological systems: the Hohokam of the Phoenix Basin

2006 ◽  
Vol 2 (2) ◽  
pp. 133-155 ◽  
Author(s):  
JOHN M. ANDERIES
Keyword(s):  
Formal Model ◽  
Irrigation System ◽  
Ecological Systems ◽  
Short Term ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Term Change ◽  
Phoenix Basin ◽  
The Phoenix

Societies frequently generate public infrastructure and institutional arrangements in order to mediate short-term environmental fluctuations. However, the social and ecological consequences of activities dealing with short-term disturbances may increase the vulnerability of the system to infrequent events or to long-term change in patterns of short-term variability. Exploring this possibility requires the study of long-term, transformational change. The archaeological record provides many examples of long-term change, such as the Hohokam who occupied the Phoenix Basin for over a thousand years and developed a complex irrigation society. In the eleventh and fourteenth centuries, the Hohokam society experienced reductions in complexity and scale possibly associated with regional climatic events. We apply a framework designed to explore robustness in coupled social-ecological systems to the Hohokam Cultural Sequence. Based on this analysis, a stylized formal model is developed to explore the possibility that the success of the Hohokam irrigation system and associated social structure may have increased their vulnerability to rare climactic shocks.

Upscaling Action Research and implications for community organizing practice

2017 ◽  
Vol 18 (4) ◽  
pp. 469-489 ◽  
Author(s):  
Melissa A Currie ◽  
Janni Sorensen
Keyword(s):  
North Carolina ◽  
Action Research ◽  
Community Organizing ◽  
Local Level ◽  
Regional Scale ◽  
Neighborhood Change ◽  
Policy Implications ◽  
Built Form ◽  
Starting Point ◽  
Research Findings

Case studies are an effective vehicle for telling important stories that may have broader implications, but how is the research study made relevant, or generalizable, to other places or events? This paper discusses the upscaling of Action Research where Action Research was the starting point at the local level that led to additional layers with larger, regional scale implications. The story behind the development process and resulting built form of Windy Ridge, a relatively new subdivision in Charlotte, North Carolina dubbed a “Neighborhood Built to Fail,” presents a compelling story. We trace the development of knowledge around three topics originating in Action Research and how we scaled those topics up to have policy implications: (1) owner occupancy and absentee landlords; (2) stability, instability, and neighborhood resiliency; and (3) zoning changes and environmental justice issues. We reflect on implications for practitioners and academics based on several years of neighborhood partnership and how Action Research can reveal structural issues at work within communities. Action Research findings provided a research- and evidence-based platform from which to advocate for neighborhood change and the motivation for the extended research. This approach produced an expanding research model emanating from Action Research data and questions originating with residents.

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