Simulating Systems-of-Systems With Agent-Based Modeling: A Systematic Literature Review

Silva, Rafael de Amorim; Braga, Rosana Teresinha Vaccare

doi:10.1109/jsyst.2020.2980896

Cited by 24 publications

(11 citation statements)

References 40 publications

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“…For example, agent-based models have been used in the healthcare, transportation, warfare, and disaster response domains. 11 Multiagent simulations with imperfect information are especially suitable for analyzing military engagements. 12…”

Section: Agent-based Modeling and Simulationmentioning

confidence: 99%

“…Large scale, distributed, and communications‐limited systems are well suited to be modeled as collections of agents. For example, agent‐based models have been used in the healthcare, transportation, warfare, and disaster response domains 11 . Multiagent simulations with imperfect information are especially suitable for analyzing military engagements 12 …”

Section: Introductionmentioning

confidence: 99%

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Modeling, simulation, and trade‐off analysis for multirobot, multioperator surveillance

Humann

Fletcher

Gerdes

2023

Systems Engineering

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As unmanned vehicles become smaller and more autonomous, it is becoming feasible to use them in large groups with comparatively few human operators. Design and analysis of such distributed systems are complicated by the many interactions among agents and phenomena of human behavior. In particular, human susceptibility to fatigue and cognitive overload can introduce errors and uncertainty into the system. In this paper, we demonstrate how advanced computational tools can help to overcome these engineering difficulties by optimizing multirobot, multioperator surveillance systems for cost, speed, accuracy, and stealth according to diverse user preferences in multiple case studies. The tool developed is a graphical user interface that returns the optimal number and mix of diverse agent types as a function of the user's trade‐off preferences. System performance prediction relies on a multiagent simulation with submodels for human operators, fixed‐wing unmanned aerial vehicles (UAVs), quadrotor UAVs, and flapping wing UAVs combined in different numbers.

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Section: Agent-based Modeling and Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling, simulation, and trade‐off analysis for multirobot, multioperator surveillance

Humann

Fletcher

Gerdes

2023

Systems Engineering

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“…Therefore, the data extraction process captured the authors' affiliations and study aim, model inputs, model development, model process and the analysis and validation methods completed by the authors. This method is similar to systematic reviews of ABMs on other social or health science research topics that focused on the study design, model specifications (agents, environment, decision rules), and model analysis (sensitivity analysis, model validation) for data extraction and synthesis [33,34,[38][39][40][41]. The data extraction tool was informed by the guiding questions outlined in the Overview, Design Concepts and Details + Decision-Making (ODD + D) protocol for ABM development, which is an adaptation of the original Overview, Design Concepts and Details (ODD) protocol developed to standardize descriptions of individual-based models (IBMs) and ABMs [5,42,43].…”

Section: Data Extractionmentioning

confidence: 99%

Agent-based modeling for migration and modern slavery research: a systematic review

et al. 2020

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This systematic review aims to synthesize how agent-based modeling (ABM) has been used in migration and modern slavery research and provide the basis to model development for social science researchers exploring the use of ABM. We searched five bibliographic databases using two terminology categories: (1) migration or modern slavery terminology; (2) complex system methods terminology. Two reviewers conducted independent article screening. Peer-reviewed articles presenting original migration or modern slavery ABMs were included. Data extraction included model development steps and model characteristics. The dataset was synthesized and compared across studies. We identified 28 articles for inclusion. Many of the ABMs tested theories and about half were based on empirical data. Model development varied considerably and reported methods were extremely opaque. Only five studies used a structured development framework. The most common model involved agents deciding whether and where to migrate and attempting migration. Climate change was a common exogenous scenario modeled. Most of the ABMs did not undergo any sensitivity analysis or validation.ABM has a greater capacity to account for heterogeneous and dynamic decision-making than more frequently applied methods in research on migration and modern slavery. However, there is still a paucity of studies adopting ABM methods. These reviewed ABMs highlight gaps in the reporting and implementing of model development. ABM is a promising technique to address many urgent and complex questions in research on migration and modern slavery to better support decision-makers, but addressing current methodological gaps is a critical first step.

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“…Out of these, ABS is the most robust and versatile approach (Hester and Tolk, 2010). Specifically, in SoS, ABS is raised as a suitable approach thanks to its bottom-up approach that allows for autonomous agent behavior (as characterized by an SoS), natural interactions between systems, and modeling of dynamic environments (Hester and Tolk, 2010;Kinder et al, 2014;Silva and Braga, 2020). ABS is a modeling approach that uses agents that operate autonomously and interact with the given context and other agents (Kinder et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…ABS is a modeling approach that uses agents that operate autonomously and interact with the given context and other agents (Kinder et al, 2014). From an engineering perspective, ABS can model complex behaviors and have agents dynamically adapt to changing contexts to reflect real-world scenarios better and achieve a close representation of the intended SoS (Silva and Braga, 2020). However, trying to program behavior that represents complex systems, such as electric vehicles with advanced dynamics, could lead to an impossible task.…”

Section: Introductionmentioning

confidence: 99%

Merging agent-based simulation and vehicle dynamics: a hybrid approach for value exploration in the mining industry

Toller Melén,

Machchhar,

Bertoni

2024

Proc. Des. Soc.

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Innovation plays a vital role in ensuring sustainable mining operations. Electrification and autonomy are two significant trends, but their implementation brings complexity at vehicle and site levels. Therefore, it is crucial to understand how these technologies impact the overall site value creation. This paper suggests a hybrid approach that combines Agent-Based Simulation and vehicle dynamics modeling to explore site configurations. By regarding a mining site as a System-of-Systems, designers can concurrently test different designs to find the optimal combination for a specific scenario.

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Simulating Systems-of-Systems With Agent-Based Modeling: A Systematic Literature Review

Cited by 24 publications

References 40 publications

Modeling, simulation, and trade‐off analysis for multirobot, multioperator surveillance

Modeling, simulation, and trade‐off analysis for multirobot, multioperator surveillance

Agent-based modeling for migration and modern slavery research: a systematic review

Merging agent-based simulation and vehicle dynamics: a hybrid approach for value exploration in the mining industry

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