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The Complexities of Agent-Based Modeling Output Analysis

Ju-Sung Lee, Tatiana Filatova, Arika Ligmann-Zielinska, Behrooz Hassani-Mahmooei, Forrest Stonedahl, Iris Lorscheid, Alexey Voinov, Gary Polhill, Zhanli Sun, Dawn C. Parker
2015 Journal of Artificial Societies and Social Simulation  
agent-based modellers contend with their model outputs, their statistical analysis, and visualization techniques. [1] We discuss challenges and offer examples for addressing them.  ...  The proliferation of agent-based models (ABMs) in recent decades has motivated model practitioners to improve the transparency, replicability, and trust in results derived from ABMs.  ...  Furthermore, our thanks go to all participants of Workshop G2 during the iEMSs 2014 Conference in San Diego. Notes  ... 
doi:10.18564/jasss.2897 fatcat:fqgukhrwpjeq5aa5vomel2y5d4

The complexities of agent-based modeling output analysis

Ju Sung Lee, Tatiana Filatova, Arika Ligmann-Zielinska, Behrooz Hassani-Mahmooei, Forrest Stonedahl, Iris Lorscheid, Alexey Voinov, Gary Polhill, Zhanli Sun, Dawn Cassandra Parker, TUHH Universitätsbibliothek, TUHH Universitätsbibliothek
The proliferation of agent-based models (ABMs) in recent decades has motivated model practitioners to improve the transparency, replicability, and trust in results derived from ABMs.  ...  Similarly, the increasing use of data and dynamics in ABMs has further enhanced the complexity of their outputs.  ...  Furthermore, our thanks go to all participants of Workshop G2 during the iEMSs 2014 Conference in San Diego. Notes  ... 
doi:10.15480/882.2697 fatcat:wd3pvke3ejbxhaaiv2ebqpprsa

Study on Agent-based Innovation Behavior Research Technique

Liu Wenrong, Xu Xiaolong
2011 Procedia Engineering  
The agent-based computer simulation method is available for complex system studying. The innovation system has characters of emergence and evolution; it is also a complex system.  ...  In order to build agent-based computer simulation model for innovation behavior studying, processes of question analysis, property abstract, model environment constructing, model agent building, model  ...  This paper is also periodic achievement of "Research of the Innovation Difference among Industries in Jilin Province" (2011B185), which is sponsored by Social Science Foundation of Jilin Province.  ... 
doi:10.1016/j.proeng.2011.08.663 fatcat:qqqrv4yvivdbpo4hk3dkjlfgfi

A scheme to analyze agent-based social simulations using exploratory data mining techniques

M. Hammad Patel, Mujtaba Ahmed Abbasi, M. Saeed, Shah Jamal Alam
2018 Complex Adaptive Systems Modeling  
Agent-based models simulating social reality generate outputs which result from a complex interplay of processes related to agents' rules of interaction and model's parameters.  ...  An agent-based model of moderate complexity will, when run across different parameters (i.e., the total number of configurations times the number of simulation runs) generates output data that could easily  ...  Acknowledgements We are thankful to the anonymous reviewers for their useful feedback and also to the reviewers of the Social Simulation 2017 conference where an earlier version of this paper was presented  ... 
doi:10.1186/s40294-018-0052-8 fatcat:msxpozeouzcn5mbz3zvazlrztm

CFBM - A Framework for Data Driven Approach in Agent-Based Modeling and Simulation [chapter]

Thai Minh Truong, Frédéric Amblard, Benoit Gaudou, Christophe Sibertin Blanc
2016 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
The successful development of the CFBM consists not only in remedying the limitation of agent-based modeling and simulation with regard to data management but also in dealing with the development of complex  ...  The introduced framework is based on the combination of Business Intelligence solution and a multi-agent based platform called CFBM (Combination Framework of Business intelligence and Multi-agent based  ...  The multi-agent analysis models are a set of tools dedicated to the analysis of multi-agent simulations, they are created based on analysis requirements and handled via the analysis interface.  ... 
doi:10.1007/978-3-319-46909-6_24 fatcat:nwhmiin6wba65pntwrt7lbh5by

'One Size Does Not Fit All': A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models

Arika Ligmann-Zielinska, Peer-Olaf Siebers, Nicholas Magliocca, Dawn C. Parker, Volker Grimm, Jing Du, Martin Cenek, Viktoriia Radchuk, Nazia N. Arbab, Sheng Li, Uta Berger, Rajiv Paudel (+4 others)
2020 Journal of Artificial Societies and Social Simulation  
Designing, implementing, and applying agent-based models (ABMs) requires a structured approach, part of which is a comprehensive analysis of the output to input variability in the form of uncertainty and  ...  Given the role of individuals in these (mostly multiscale) systems, scientists o en employ entity-based models, referred to as agent-based models (ABMs) in social sciences and engineering, and individual-based  ...  They determined that regression analysis is not a complete -or even sometimes a correct -tool for analysis of the sensitivity of a model representing a complex system.  ... 
doi:10.18564/jasss.4201 fatcat:v3linogbsrar5kyuiz3gupvuf4

Which Sensitivity Analysis Method Should I Use for My Agent-Based Model?

Guus ten Broeke, George van Voorn, Arend Ligtenberg
2016 Journal of Artificial Societies and Social Simulation  
Existing methodologies of sensitivity analysis may be insufficient for a proper analysis of Agent-based Models (ABMs).  ...  This limits the information content that follows from the classical sensitivity analysis methodologies that link model output to model input.  ...  The lack of fit resulting from the inherent complexity of ABMs limits the usefulness of regression-based sensitivity analysis for these models, as the systems which they are used to model are complex adaptive  ... 
doi:10.18564/jasss.2857 fatcat:u2alggvaz5e2rbh2eb2lxjiuyu

Reinforcement learning on complex visual stimuli

Niko Wilbert, Robert Legenstein, Mathias Franzius, Laurenz Wiskott
2009 BMC Neuroscience  
Given this complex input, the model should extract the position and direction of the agent, and the position of the target.  ...  Animals are confronted with the problem of initiating motor actions based on very complex sensory input.  ...  Given this complex input, the model should extract the position and direction of the agent, and the position of the target.  ... 
doi:10.1186/1471-2202-10-s1-p90 fatcat:gyplrnvdnnemjmnuz2mwe2fo4i

Towards Agent-Based Model Specification in Smart Grid: A Cognitive Agent-based Computing Approach [article]

Waseem Akram, Muaz A. Niazi, Laszlo Barna Iantovics
2017 arXiv   pre-print
One way to study complex systems is by using the agent-based modeling (ABM) paradigm. An ABM is a way of representing a complex system of autonomous agents interacting with each other.  ...  We propose an ABM by using a combination of agent-based and complex network-based approaches. For ABM specification, we use ODD and DREAM specification approaches.  ...  The Descriptive agent-based model level is the process of presenting ABM specification in the form of pseudo-code, a complex network of the model and social network analysis.  ... 
arXiv:1710.03189v2 fatcat:7cnov652yngnfcq22xqfiss25q

Agent-Based Modelling of Social-Ecological Systems: Achievements, Challenges, and a Way Forward

Jule Schulze, Birgit Müller, Jürgen Groeneveld, Volker Grimm
2017 Journal of Artificial Societies and Social Simulation  
Additionally, a particular challenge for model evaluation of agent-based modelling is the quality assessment of the representation of decision-making, particularly when modelling complex decisions made  ...  Agent-based models (ABMs) have therefore already been widely used to study SES. However, ABMs of SES are by their very nature complex.  ...  BM was supported by the German Federal Ministry of Education and Research (BMBFd LN A) within the Junior Research Group POLISES.  ... 
doi:10.18564/jasss.3423 fatcat:bds2dbp2yjgujishk6leskadae

Using machine learning as a surrogate model for agent-based simulations

Claudio Angione, Eric Silverman, Elisabeth Yaneske, Roland Bouffanais
2022 PLoS ONE  
In this proof-of-concept work, we evaluate the performance of multiple machine-learning methods as surrogate models for use in the analysis of agent-based models (ABMs).  ...  Analysing agent-based modelling outputs can be challenging, as the relationships between input parameters can be non-linear or even chaotic even in relatively simple models, and each model run can require  ...  Introduction In this paper, we investigate the use of machine-learning-based surrogate modelling for the analysis of agent-based models (ABMs).  ... 
doi:10.1371/journal.pone.0263150 pmid:35143521 pmcid:PMC8830643 fatcat:6on2y5yq45dsdmx7ss5ivc64j4

Validation techniques of agent based modelling for geospatial simulations

M. Darvishi, G. Ahmadi
2014 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Agent-based modelling and simulation (ABMS) is a new modelling method comprising of multiple interacting agent.  ...  Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods.  ...  Some especial properties of Agent based modeling such as learning process; interactions between other agents, data independence, heterogeneity and complexity of the agents make the validation of ABM difficult  ... 
doi:10.5194/isprsarchives-xl-2-w3-91-2014 fatcat:w3n4tnnlqfcyfkvxmyitkxqyp4

IEEE Access Special Section Editorial: Recent Advances on Hybrid Complex Networks: Analysis and Control

Jianquan Lu, Daniel W. C. Ho, Tingwen Huang, Jurgen Kurths, Ljiljana Trajkovic
2021 IEEE Access  
of linear multi-agent systems based on distributed event-triggered control strategies.  ...  consensus of high-order agents with unknown high-frequency gain signs (UHFGSs) in switching topologies and investigates the output leaderless consensus of heterogeneous agents with UHFGSs.  ... 
doi:10.1109/access.2021.3087971 fatcat:zxlj7vjlsjfifist4ivjm3qfmy

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection

Maksudul Alam, Xinwei Deng, Casandra Philipson, Josep Bassaganya-Riera, Keith Bisset, Adria Carbo, Stephen Eubank, Raquel Hontecillas, Stefan Hoops, Yongguo Mei, Vida Abedi, Madhav Marathe (+1 others)
2015 PLoS ONE  
Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system.  ...  Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM.  ...  Acknowledgments We thank our external collaborators and members of the Network Dynamics and Simulation Science Laboratory (NDSSL) and the Nutritional Immunology and Molecular Medicine Laboratory (NIMML  ... 
doi:10.1371/journal.pone.0136139 pmid:26327290 pmcid:PMC4556515 fatcat:yvccewop3fforhjfw6jwi5ujky

Behavioral Agent Testing of Distributed Information Systems

Oleksandr Martynyuk, Oleksandr Drozd, Hanna Stepova, Viktor Antonyuk, Dmitry Martynyuk
2020 International Workshop on Information-Communication Technologies & Embedded Systems  
To ensure autonomy and mobility, the agent-based check model defines the resource model of the component deployment environment, models of its goals and test strategies, signatures of multi-agent operations  ...  For the cooperation of agent-based check models in the network and multi-level interaction of their reactive and deliberative components, there are cooperative definitions for resource models of placement  ...  Generally, these limits are determined by exponential (NP-complex) dependences of the complexity of such an analysis from the dimension of input models [15] [16] [17] [18] [19] .  ... 
dblp:conf/ictes/MartynyukDSAM20 fatcat:434fnoqqm5dszaoohpi5bzjq2i
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