Observations on the practice and profession of modeling and simulation: A survey approach

SIMULATION ◽  
2017 ◽  
Vol 94 (6) ◽  
pp. 493-506 ◽  
Author(s):  
Jose J Padilla ◽  
Saikou Y Diallo ◽  
Christopher J Lynch ◽  
Ross Gore
Keyword(s):  
Social Sciences ◽  
Modeling And Simulation ◽  
Model Simulation ◽  
Discrete Event ◽  
Conceptual Modeling ◽  
Educational Background ◽  
Three Dimensions ◽  
Trial And Error ◽  
Agent Based ◽  
Survey Approach

This paper reports on a survey capturing modelers’ perspectives of Modeling and Simulation (M&S). The survey was completed by a total of 283 respondents from the M&S community with 167 fully completed surveys and 151 respondents identified as model builders. Participants include people from government, academia, and industry in varied roles ranging from researchers to business developers. Respondents also represent a diverse educational background ranging from oceanography, social sciences, and engineering. The survey focuses on three dimensions namely: (a) models and simulations, (b) participants, and (c) how participants interact with models/simulations. We provide six observations from the data analysis: there is no dominating paradigm in M&S, the agent-based community is distinct from the discrete-event community, conceptual modeling is the art of M&S, simulation verification is mostly a trial and error activity, validate by all means necessary, and model accreditation is still too uncommon. A key finding from these observations is the identification of an over-reliance on informal methods for conceptualization and verification in M&S. We posit that this over-reliance on informal methods challenges model/simulation validity.

RCR Report of “A Language for Agent-Based Discrete-Event Modeling and Simulation of Linked Lives”

2022 ◽  
Vol 32 (1) ◽  
pp. 1-4
Author(s):  
Romolo Marotta
Keyword(s):  
Modeling And Simulation ◽  
Discrete Event ◽  
Agent Based ◽  
Event Modeling ◽  
Term Retention ◽  
Linked Lives ◽  
Long Term Retention

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.

A modeling framework for the application of multi-paradigm simulation methods

SIMULATION ◽  
2019 ◽  
Vol 96 (1) ◽  
pp. 55-73 ◽  
Author(s):  
Konstantinos Mykoniatis ◽  
Anastasia Angelopoulou
Keyword(s):  
System Dynamics ◽  
Modeling And Simulation ◽  
Discrete Event ◽  
Simulation Models ◽  
Discrete Event System ◽  
Modeling Framework ◽  
Agent Based ◽  
Event System ◽  
Generic Modeling ◽  
Generic Relationships

Decisions about modeling and simulation (M&S) of real-world systems need to be evaluated prior to implementation. Discrete Event, System Dynamics, and Agent Based are three different modeling and simulation approaches widely applied to enhance decision-making of M&S of these systems. Combining and/or integrating these methods can provide solutions to a plethora of systems’ problems. However, current solutions and frameworks do not provide guidance for selecting and deploying M&S models. Hence, the aim of this work is to present a generic modeling framework for combining and/or integrating Discrete Event, System Dynamics, and Agent Based simulation approaches. The framework is termed multi-paradigm modeling framework (MPMF). In this paper, we describe the research methodology that was followed for the development of MPMF, the different phases of MPMF, and the generic relationships of forming and deploying multi-paradigm simulation models. Then we evaluate the framework by using it for the implementation of a universal task analysis simulation model (UTASiMo). The MPMF provided guidance on what methods need to be incorporated into the UTASiMo models, what information is exchanged among those models, and how these models are connected and interact with each other.

A Language for Agent-based Discrete-event Modeling and Simulation of Linked Lives

2022 ◽  
Vol 32 (1) ◽  
pp. 1-26
Author(s):  
Oliver Reinhardt ◽  
Tom Warnke ◽  
Adelinde M. Uhrmacher
Keyword(s):  
Modeling And Simulation ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Domain Specific ◽  
Event Modeling ◽  
Linked Lives ◽  
External Domain ◽  
Concrete Language

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.

Sign in / Sign up

Export Citation Format

Share Document