Tutorial on Agent-Based Modeling and Simulation PART 2: How to Model with Agents

Macal,

doi:10.1109/wsc.2006.323040

Cited by 316 publications

(167 citation statements)

References 13 publications

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“…As agents can be very detailed, they also require more detailed data. However, as Macal and North (2006) point out, data exists on a higher level of detail today, which makes ABDS more applicable. If data is not available, the results of the model are also unreliable.…”

Section: Discussionmentioning

confidence: 99%

Agent based decision support in the supply chain context

Hilletofth

Lättilä

2012

Industrial Management &Amp; Data Systems

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Purpose: The purpose of this paper is to investigate the benefits and the barriers of agent based decision support (ABDS) systems in the supply chain context. Design/methodology/approach: Two ABDS systems have been developed and evaluated. The first system concerns a manufacturing supply chain while the second concerns a service supply chain. The systems are based on actual case companies. Findings:This research shows that the benefits of ABDS systems in the supply chain context include the possibility to increase versatility of system architecture, to improve supply chain visibility, to conduct experiments and what-if analyses, to improve the understanding of the real system, and the possibility to improve communication within and between organizations in the supply chain. The barriers of ABDS systems in the supply chain context include the difficulty to access data from partners in the supply chain, the difficulty to access data on a higher level of granularity, and the difficulty to retrieve data from other information systems. Research limitations/implications:The research is explorative in nature therefore empirical data from similar and other research settings should be gathered to reinforce the validity of the findings. Practical implications:This research provides knowledge and insights on how ABDS systems may be developed and used in the supply chain context and demonstrates its main benefits and barriers. Originality/value:This research expands the current research of benefits of ABDS systems to the supply chain domain and also addresses the barriers of ABDS systems to a larger extent than previous research. Comparisons to other simulation based decision support systems are also given.

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Section: Discussionmentioning

confidence: 99%

Agent based decision support in the supply chain context

Hilletofth

Lättilä

2012

Industrial Management &Amp; Data Systems

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“…4) In choosing the agents it has been noted that agents have the most homogeneity with the identified behavior (Macal and North, 2006b;Wilensky and Rand, 2015).…”

Section: Identification Of the Key Agents From The Final List Of Paramentioning

confidence: 99%

Modeling Socio-Ecological Structure of Local Communities Participation for Managing Livestock Drinking Water Using the Agent-Based Approach

Islami¹,

Sadoddin²,

Barani³

et al. 2017

Appl Ecol Env Res

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Abstract. The agent-based modelling (ABM) can illuminate how multi-dimensional process of public participation emerges from simple behavior rules. It can model the participation process which is too complicated using congenital approaches. In the present research, the social structure of human participation in managing livestock drinking water of arid rangelands in Yazd Province, Iran, was designed using the four steps of ABM. This study provides a true understanding of interactions of four agents including government, livestock beneficiaries, natural resources organization and NGOs with each other and with the natural environment. In order to achieve conceptual proof, the Delphi technique was applied for stepwise identification of agents and their real behaviors. Additionally, quantification of decision elements and decision-making hypotheses was examined using the Analytical Network Process (ANP). By confirming the conceptual validity of decision-making hypotheses through network analysis, the conceptual model was confirmed. The analysis demonstrates that "low income of livestock beneficiaries", "successive droughts and low rainfall" and "weakness of NGOs", with normal weights of 0.31, 0.15, and 0.09, respectively are three major drivers for problem of weak participation among local communities in the study area. This research is an example of incorporating the ABM approach in settling problems encountered with social system.

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“…• Agent-based models could be used to identify simple interaction rules that can lead to different emergent population level behaviors like flocking (Macal and North, 2006;Railsback and Grimm, 2011). …”

Section: Exploring Unknown Possibilitiesmentioning

confidence: 99%

An invitation to modeling: building a community with shared explicit practices

Dahlquist

Aikens

Dauer

et al. 2017

Preprint

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Models and the process of modeling are fundamental to the discipline of biology, and therefore should be incorporated into undergraduate biology courses. In this essay, we draw upon the literature and our own teaching experiences to provide practical suggestions for how to introduce models and modeling to introductory biology students. We begin by demonstrating the ubiquity of models in biology, including representations of the process of science itself. We advocate for a model of the process of science that highlights parallel tracks of mathematical and experimental modeling investigations. With this recognition, we suggest ways in which instructors can call students’ attention to biological models more explicitly by using modeling language, facilitating metacognition about the use of models, and employing model-based reasoning. We then provide guidance on how to begin to engage students in the process of modeling, encouraging instructors to scaffold a progression to mathematical modeling. We use the Hardy-Weinberg Equilibrium model to provide specific pedagogical examples that illustrate our suggestions. We propose that by making even a small shift in the way models and modeling are discussed in the classroom, students will gain understanding of key biological concepts, practice realistic scientific inquiry, and build quantitative and communication skills.

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Tutorial on Agent-Based Modeling and Simulation PART 2: How to Model with Agents

Cited by 316 publications

References 13 publications

Agent based decision support in the supply chain context

Agent based decision support in the supply chain context

Modeling Socio-Ecological Structure of Local Communities Participation for Managing Livestock Drinking Water Using the Agent-Based Approach

An invitation to modeling: building a community with shared explicit practices

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