scholarly journals Agent-Based Simulation and Its Application to Analyze Combat Effectiveness in Network-Centric Warfare Considering Communication Failure Environments

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Jaeyeong Lee ◽  
Sunwoo Shin ◽  
Moonsung Park ◽  
Chongman Kim
Keyword(s):  
Communication Network ◽  
Agent Based Modeling ◽  
Alternative Measure ◽  
Agent Based Simulation ◽  
Communication Failure ◽  
Agent Based ◽  
Modeling Process ◽  
Effectiveness Analysis ◽  
Combat Effectiveness ◽  
Modern Warfare

Many parts of platforms are expected to be replaced by unmanned systems in modern warfare. All the assets and supporting vehicles are linked to each other with a communication network, and it is called the network-centric warfare environment. Hence, it is critical when communication failure occurs during engagement in ground battlefield because this failure will directly affect overall combat effectiveness of one’s owned assets. However, research regarding communication failure issues is scarce. We herein propose a new agent-based modeling process to measure the overall combat effectiveness combined with communication success ratio, based on the terrain condition of the ground engagement. Additionally, we provide the effectiveness analysis result when a communication repeater is applied during communication failure as an alternative measure.

First Steps Towards RAT: A Protocol for Documenting Data Use in the Agent-Based Modeling Process

2021 ◽  
pp. 257-261
Author(s):  
Peer-Olaf Siebers ◽  
Sebastian Achter ◽  
Cristiane Palaretti Bernardo ◽  
Melania Borit ◽  
Edmund Chattoe-Brown
Keyword(s):  
Data Use ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Modeling Process

Computational Intelligence as a Platform for a Data Collection Methodology in Management Science

2011 ◽  
pp. 38-54
Author(s):  
Kristina R. Jespersen
Keyword(s):  
Data Collection ◽  
Computational Intelligence ◽  
Role Play ◽  
Management Science ◽  
Agent Based Modeling ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Technological Support ◽  
Business Applications ◽  
New Generation

With an increased focus in management science on how to collect data close to the real world of managers, we consider how agent-based simulations have interesting prospects that are usable for the design of business applications aimed at the collection of data. As an example of a new generation of data collection methodologies, this chapter discusses and presents a behavioral simulation founded in the agent-based simulation life cycle and supported by Web technology. With agent-based modeling the complexity of the method can be increased without limiting the research as a result of limited technological support. This makes it possible to exploit the advantages of a questionnaire, an experimental design, a role-play and a scenario, gaining the synergy of a combination of these methodologies. At the end of the chapter an example of a simulation is presented for researchers and practitioners to study. 1

QUANTIFYING THE IMPACT OF CONGESTION ON CONSTRUCTION LABOR PRODUCTIVITY USING AGENT-BASED MODELING

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Mohammad Rahal ◽  
Hiam Khoury
Keyword(s):  
Labor Productivity ◽  
Spatial Configuration ◽  
Quantitative Model ◽  
Agent Based Modeling ◽  
Direct Impact ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Future Work ◽  
The Impact ◽  
Construction Trades

Several findings from the construction field stipulate that productivity falloffs are primarily management-related; however, this notion does not consider the direct impact of these same management decisions on the workers themselves. For instance, the planning of the workspace layout delves in a spatial configuration which if not properly managed can potentially result in congestion that, in turn, directly affects labor productivity. Previous research efforts developed models to analyze the effect of congestion on labor productivity but failed to capture all the complexities of this mechanism and its dynamics. Therefore, this paper puts forward the groundwork of an agent-based simulation model (ABM) and presents work targeted at quantifying the impact of congestion on the productivity of construction crews. More specifically, the ABM model takes into account two construction trades working in the same area and tackles five scenarios each depicting different congestion and interaction levels. At the heart of this simulation is a quantitative model that defines essential congestion metrics and outputs space interference values. Experiments were conducted and results highlighted that the higher the space interference values the less productive the crews become. Additionally, these values will constitute an integral part in future work when studying the impact of congestion on the crews' learning curve, whereby the latter being a major gauge for levels of productivity.

On the contributions and the validation of an agent-based simulation model of innovation diffusion

2016 ◽  
Vol 50 (3/4) ◽  
pp. 647-657 ◽  
Author(s):  
Mohammad G. Nejad
Keyword(s):  
Simulation Modeling ◽  
Agent Based Modeling ◽  
Test Theory ◽  
Future Research ◽  
Agent Based Simulation ◽  
Content Type ◽  
Agent Based ◽  
Points Of View ◽  
Complex Phenomena ◽  
Specific Paper

Purpose This paper provides an overview of agent-based modeling and simulation (ABMS) and evaluates the questions that have been raised regarding the “assumptions and mechanisms used” by a well-cited paper that has used this methodology. Design/methodology/approach This work provides a review of agent-based simulation modeling and its capabilities to advance and test theory. The commentary then evaluates and addresses the raised questions and reservations. Findings Agent-based modeling offers unique capabilities that can be used to explore complex phenomena in business and marketing. Some of the raised reservations may be considered as directions for future research. However, the criticisms are for most part unsupported by existing research and do not undermine the contributions of the paper that is being discussed. Practical implications Given its relative novelty, reservations regarding agent-based simulation modeling are quite natural. Discussions like this one would bring together different points of view and lead to a better understanding of how using ABMS can benefit academia and industry. Originality/value This commentary is part of an intellectual dialogue that seeks to provide different points of view about agent-based simulation modeling using a specific paper as an example.

scholarly journals GETTING AWAY FROM NUMBERS: USING QUALITATIVE OBSERVATION FOR AGENT-BASED MODELING

2008 ◽  
Vol 11 (02) ◽  
pp. 175-185 ◽  
Author(s):  
LU YANG ◽  
NIGEL GILBERT
Keyword(s):  
Social Sciences ◽  
Quantitative Data ◽  
Qualitative Data ◽  
Participant Observation ◽  
Agent Based Modeling ◽  
Agent Based Models ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Qualitative Observation

Although in many social sciences there is a radical division between studies based on quantitative (e.g. statistical) and qualitative (e.g. ethnographic) methodologies and their associated epistemological commitments, agent-based simulation fits into neither camp, and should be capable of modelling both quantitative and qualitative data. Nevertheless, most agent-based models (ABMs) are founded on quantitative data. This paper explores some of the methodological and practical problems involved in basing an ABM on qualitative participant observation and proposes some advice for modelers.

Discrete-event simulation and agent-based modeling in the tasks of the school informatics course

2020 ◽  
Vol 1 (9) ◽  
pp. 4-13
Author(s):  
N. V. Klimina ◽  
I. A. Morozov
Keyword(s):  
Extracurricular Activities ◽  
Discrete Event ◽  
Simulation Models ◽  
Agent Based Modeling ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Event Simulation ◽  
Cellular Environment ◽  
Scope Of Application ◽  
Biological Simulation

In order to study processes and phenomena, it is necessary to create their models. The most interesting and valuable for the analysis of current situations are models that describe processes as if they were happening in reality. These are the so-called simulation models. The scope of application of simulation models is extensive. The most in demand are economic, sociological and biological simulation models. The relevance of simulation is obvious, and it is natural that the theme of simulation is present in the content of the school informatics course. The article provides guidelines for studying the basics of modeling in a school informatics course related to the creation and research of discrete-event and agent-based simulation models. Examples of tasks recommended for consideration in the 9–11th grades at informatics lessons or in extracurricular activities are given, these are task based on the information-cybernetic approach, implemented in the PascalABC environment, and the task using a cellular automaton, implemented in the Cellular environment.

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