A python framework for multi-agent simulation of networked resource systems

Knox, Stephen; Meier, Philipp; Yoon, Jim; Harou, Julien J.

doi:10.1016/j.envsoft.2018.01.019

Cited by 37 publications

(19 citation statements)

References 46 publications

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“…The JWM adopts a systems-based, multiagent, modular approach, in which each module represents a specific component of Jordan’s water system. The model is implemented in an object-oriented software architecture ( 37 ). The individual modules are developed and calibrated independently, and subsequently integrated by identifying significant interactions and feedbacks between system components.…”

Section: Methodsmentioning

confidence: 99%

“…The JWM combines these components into an integrated multiagent model for evaluation of nationwide freshwater security, rigorously attempting to capture all significant physical and human features and their interactions across an entire country’s water sector. The integrated model adopts a modular structure and is implemented in an object-oriented software architecture ( 37 ), in which each module represents a specific component of Jordan’s water system ( Materials and Methods and SI Appendix , Methods ). The model is run from 2006 to 2014 to represent historical conditions (validation results are included in SI Appendix , Model Validation ) and from 2016 to 2100 to simulate future conditions, proceeding on monthly time increments.…”

Section: Coupled Human–natural Systems Modeling Approachmentioning

confidence: 99%

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A coupled human–natural system analysis of freshwater security under climate and population change

Yoon

Klassert

Selby

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Limited water availability, population growth, and climate change have resulted in freshwater crises in many countries. Jordan’s situation is emblematic, compounded by conflict-induced population shocks. Integrating knowledge across hydrology, climatology, agriculture, political science, geography, and economics, we present the Jordan Water Model, a nationwide coupled human–natural-engineered systems model that is used to evaluate Jordan’s freshwater security under climate and socioeconomic changes. The complex systems model simulates the trajectory of Jordan’s water system, representing dynamic interactions between a hierarchy of actors and the natural and engineered water environment. A multiagent modeling approach enables the quantification of impacts at the level of thousands of representative agents across sectors, allowing for the evaluation of both systemwide and distributional outcomes translated into a suite of water-security metrics (vulnerability, equity, shortage duration, and economic well-being). Model results indicate severe, potentially destabilizing, declines in freshwater security. Per capita water availability decreases by approximately 50% by the end of the century. Without intervening measures, >90% of the low-income household population experiences critical insecurity by the end of the century, receiving <40 L per capita per day. Widening disparity in freshwater use, lengthening shortage durations, and declining economic welfare are prevalent across narratives. To gain a foothold on its freshwater future, Jordan must enact a sweeping portfolio of ambitious interventions that include large-scale desalinization and comprehensive water sector reform, with model results revealing exponential improvements in water security through the coordination of supply- and demand-side measures.

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Section: Methodsmentioning

confidence: 99%

Section: Coupled Human–natural Systems Modeling Approachmentioning

confidence: 99%

A coupled human–natural system analysis of freshwater security under climate and population change

Yoon

Klassert

Selby

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

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“…A MAS model is then developed using the Pynsim architecture (Knox et al 2018). It relies on a network made of nodes and arcs, which is particularly useful to represent spatially distributed agents inside the same river basin system (Harou et al 2009).…”

Section: Multi-agent Simulationmentioning

confidence: 99%

“…Nodes symbolize reservoirs, aquifers, consumption sites, and diversion systems; and arcs symbolize rivers, pipes, canals, and groundwater transfers. The main asset of Pynsim, though, lies in the capacity to define different institutional levels of managing agents, from individual actors who manage one site to institutions who supervise interactions within the water resources system (Knox et al 2018). These agents are integrated in a single computing framework where human and institutional decisions complement the physical processes from a traditional arcs and nodes representation.…”

Section: Multi-agent Simulationmentioning

confidence: 99%

Quantitative Assessment of Contested Water Uses and Management in the Conflict-Torn Yarmouk River Basin

Avisse

Tilmant

Rosenberg

et al. 2020

J. Water Resour. Plann. Manage.

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The Yarmouk River basin is shared between Syria, Jordan, and Israel. Since the 1960s, Yarmouk River flows have declined more than 85% despite the signature of bilateral agreements. Syria and Jordan blame each other for the decline and have both developed their own explanatory narratives: Jordan considers that Syria violated their 1987 agreement by building more dams than what was agreed on, while Syria blames climate change. In fact, as the two countries do not share information, neither on hydrological flows nor on water management, it is increasingly difficult to distinguish between natural and anthropogenic factors affecting the flow regime. Remote sensing and multiagent simulation are combined to carry out an independent, quantitative, analysis of Jordanian and Syrian competing narratives and show that a third cause for which there is no provision in the bilateral agreements actually explains much of the changes in the flow regime: groundwater over-abstraction by Syrian highland farmers.

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“…Multi-agent simulation is a simulation model that emphasizes individual agents as sub-components. Individual agents interact with each other to influence the whole system [19]. Previous research has shown that multi-agent methods can solve complex system problems [20] [22].…”

Section: Design Of Multi-agent Simulation Modelmentioning

confidence: 99%

Multi-Agent Simulation in the Inter-Organizational Trust Model and Knowledge Sharing in the Automotive Industry

Rizana

Ramadhan²

2019

JTI

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Two organizations can share knowledge to determine the success of their collaboration. Effectiveness in sharing knowledge affect the organizational performance and trust between organizations. This study aims to identify the implementation of multi-agent simulations to increase confidence in sharing knowledge between organizations. A multi-agent simulation approach was used in this study. The research model was adopted from previous research. Several hypotheses and path coefficients had tested in simulation models. The results of this study showed that multi-agent simulation is suitable to be implemented as a problem-solving method for a complex problem such as knowledge sharing. Besides, this study found the role of individual factors such as likability and expertise on the success of sharing knowledge between organizations.

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A python framework for multi-agent simulation of networked resource systems

Cited by 37 publications

References 46 publications

A coupled human–natural system analysis of freshwater security under climate and population change

A coupled human–natural system analysis of freshwater security under climate and population change

Quantitative Assessment of Contested Water Uses and Management in the Conflict-Torn Yarmouk River Basin

Multi-Agent Simulation in the Inter-Organizational Trust Model and Knowledge Sharing in the Automotive Industry

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