Agent Based
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2022 ◽  
Vol 32 (1) ◽  
pp. 1-26
Oliver Reinhardt ◽  
Tom Warnke ◽  
Adelinde M. Uhrmacher

In agent-based modeling and simulation, discrete-time methods prevail. While there is a need to cover the agents’ dynamics in continuous time, commonly used agent-based modeling frameworks offer little support for discrete-event simulation. Here, we present a formal syntax and semantics of the language ML3 (Modeling Language for Linked Lives) for modeling and simulating multi-agent systems as discrete-event systems. The language focuses on applications in demography, such as migration processes, and considers this discipline’s specific requirements. These include the importance of life courses being linked and the age-dependency of activities and events. The developed abstract syntax of the language combines the metaphor of agents with guarded commands. Its semantics is defined in terms of Generalized Semi-Markov Processes. The concrete language has been realized as an external domain-specific language. We discuss implications for efficient simulation algorithms and elucidate benefits of formally defining domain-specific languages for modeling and simulation.

2022 ◽  
Vol 32 (1) ◽  
pp. 1-4
Romolo Marotta

The artifact evaluated in this report is relevant to the article. In fact, it allows us to run the experiments and reproduce figures, and the dependencies are documented. The process to regenerate data presented in the article completes correctly, and the results are reproducible. Additionally, the authors have uploaded their artifact on permanent repositories, which ensures a long-term retention. This article can thus receive the Artifacts Available , Artifacts Evaluated–Reusable , and Results Reproduced badges.

Fa Zhang ◽  
Shi-Hui Wu ◽  
Zhi-Hua Song

Multi-agent based simulation (MABS) is an important approach for studying complex systems. The Agent-based model often contains many parameters, these parameters are usually not independent, with differences in their range, and may be subjected to constraints. How to use MABS investigating complex systems effectively is still a challenge. The common tasks of MABS include: summarizing the macroscopic patterns of the system, identifying key factors, establishing a meta-model, and optimization. We proposed a framework of experimental design and data mining for MABS. In the framework, method of experimental design is used to generate experiment points in the parameter space, then generate simulation data, and finally using data mining techniques to analyze data. With this framework, we could explore and analyze complex system iteratively. Using central composite discrepancy (CCD) as measure of uniformity, we designed an algorithm of experimental design in which parameters could meet any constraints. We discussed the relationship between tasks of complex system simulation and data mining, such as using cluster analysis to classify the macro patterns of the system, and using CART, PCA, ICA and other dimensionality reduction methods to identify key factors, using linear regression, stepwise regression, SVM, neural network, etc. to build the meta-model of the system. This framework integrates MABS with experimental design and data mining to provide a reference for complex system exploration and analysis.

2022 ◽  
Vol 103 ◽  
pp. 103147
M.R.K. Siam ◽  
Haizhong Wang ◽  
Michael K. Lindell ◽  
Chen Chen ◽  
Eleni I. Vlahogianni ◽  

Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-1
Mario A. Bertella ◽  
Jonathas N. Silva ◽  
André L. Correa ◽  
Didier Sornette

Sylvie Geisendorf ◽  
Christian Klippert

AbstractThe paper proposes an agent-based evolutionary ecological-economic model that captures the link between the economy and the ecosystem in a more inclusive way than standard economic optimization models do. We argue that an evolutionary approach is required to understand the integrated dynamics of both systems, i.e. micro–macro feedbacks. In the paper, we illustrate that claim by analyzing the non-triviality of finding a sustainability policy mix as a use case for such a coupled system. The model has three characteristics distinguishing it from traditional environmental and resource economic models: (1) it implements a multi-dimensional link between the economic and the ecological system, considering side effects of production, and thus combines the analyses of environmental and resource economics; (2) following literature from biology, it uses a discrete time approach for the biological resource allowing for the whole range of stability regimes instead of artificially stabilizing the system, and (3) it links this resource system to an evolving, agent-based economy (on the basis of a Nelson-Winter model) with bounded rational decision makers instead of the standard optimization model. The policy case illustrates the relevance of the proposed integrated assessment as it delivers some surprising results on the effects of combined and consecutively introduced policies that would go unnoticed in standard models.

Lena Gerdes ◽  
Bernhard Rengs ◽  
Manuel Scholz-Wäckerle

AbstractThe world economy crucially depends on multi-layered value chains with high degrees of sector-related specialization. Its final products are of international character and serve the needs and wants of the global citizen. However, many production processes are causing severe damage to the environment and moreover create health hazard for workers and local populations. This research article focuses on the increasing global unequal economic- and ecological exchange, fundamentally embedded in international trade. Resource extraction and labor conditions in the Global South as well as the implications for climate change originating from industry emissions in the North are investigated with an agent-based model. The model serves as a testbed for simulation experiments with evolutionary political economic policies. An international institution is introduced sanctioning the polluting extractivist sector in the Global South as well as the emitting industrial capital good producers in the North with the aim of subsidizing innovation reducing environmental and social impacts. Both regions are modelled as macroeconomic complex adaptive systems where international trade is restricted to a three-sector value chain, originating from mining resources in the South that are traded to capital good producers in the North crafting machinery which is eventually traded to consumer good firms, both in the North and South. The main outcome of the study is that sanctions alone are not effective in countering unequal exchange. They only make a difference in combination with subsidies for innovation activities, which are protecting labor and reducing local pollution in mines as well as reducing carbon-emissions in capital good production.

2022 ◽  
David MJ Naimark ◽  
Juan David Rios ◽  
Sharmistha Mihsra ◽  
Beate Sander ◽  
Petros Pechlivanoglou

Importance: Universal paid sick-leave (PSL) policies have been implemented in jurisdictions to mitigate the spread of SARS-CoV-2. However empirical data regarding health and economic consequences of PSL policies is scarce. Objective: To estimate effects of a universal PSL policy in Ontario, Canada's most populous province. Design: An agent-based model (ABM) to simulate SARS-CoV-2 transmission informed by data from Statistics Canada, health administrative sources, and from the literature. Setting: Ontario from January 1st to May 1st, 2021. Participants: A synthetic population (1 million) with occupation and household characteristics representative of Ontario residents (14.5 million). Exposure: A base case of existing employer-based PSL alone versus the addition of a 3- or 10-day universal PSL policy to facilitate testing and self-isolation among workers infected with SARS-CoV-2 themselves or because of infected household members. Main Outcome(s) and Measure(s): Number of SARS-CoV-2 infections and COVID-19 hospitalizations, worker productivity, lost wages, and presenteeism (going to a workplace while infected).

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