Selected Publications

Bae, J. W., & Moon, I. C. (2016). LDEF Formalism for Agent-Based Model Development. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(6), 793–808.

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Bae, J. W., & Moon, I. C. (2016). LDEF Formalism for Agent-Based Model Development. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(6), 793–808. http://doi.org/10.1109/TSMC.2015.2461178

 

 

Abstract : 

 As agent-based models (ABMs) are applied to various domains, the efficiency of model development has become an important issue in its applications. The current practice is that many models are developed from scratch, while they could have been built by reusing existing models. Moreover, when models need reconfiguration, they often need to be rebuilt significantly. These problems reduce the development efficiency and ultimately damage the efficacy of ABM. This paper partially resolves the challenges of model reusability from the systems engineering approach. Specifically, we propose a formalism-based ABM development and demonstrate its potential to promote model reuses. Our formalism, named large-scale, dynamic, extensible, and flexible (LDEF) formalism, encourages the building of a larger model by the composition of modularly developed components. Also, LDEF is tailored to the ABM contexts to represent the agent's action procedure and support the dynamic changes of their interactions. This paper shows that LDEF improves the model reusability in ABM development through its practical examples and theoretical discussions.

 

 

@ARTICLE{7192627, 
author={J. W. Bae and I. C. Moon}, 
journal={IEEE Transactions on Systems, Man, and Cybernetics: Systems}, 
title={LDEF Formalism for Agent-Based Model Development}, 
year={2016}, 
volume={46}, 
number={6}, 
pages={793-808}, 
keywords={Artificial intelligence;Biological system modeling;Context;Context modeling;Couplings;Agent-based model (ABM) formalism;efficient ABM development;formalism-based model development;model reusability}, 
doi={10.1109/TSMC.2015.2461178}, 
ISSN={2168-2216}, 
month={June},}

 

 

Source Website : 

 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7192627&tag=1

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14 J. W. Bae et al., "Layered Behavior Modeling via Combining Descriptive and Prescriptive Approaches: A Case Study of Infantry Company Engagement," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, no. 7, pp. 2551-2565, July 2020 file
13 Kyungwoo Song, Wonsung Lee, and Il-Chul Moon. Neural Ideal Point Estimation Network. AAAI Conference on Artificial Intelligence (AAAI 2018). New Orleans. Feb 2-7 file
12 Sungrae Park, Jun-Keon Park, Su-Jin Shin, and Il-Chul Moon. Adversarial Dropout for Supervised and Semi-Supervised Learning. AAAI Conference on Artificial Intelligence (AAAI 2018). New Orleans. Feb 2-7 file
11 Wonsung Lee, Kyungwoo Song, and Il-Chul Moon. Augmented Variational Autoencoders for Collaborative Filtering with Auxiliary Information, ACM Conference on Information and Knowledge Management (CIKM 2017), Singapore, Nov 6-10 file
10 J. W. Bae et al., "Evaluation of Disaster Response System Using Agent-Based Model With Geospatial and Medical Details," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 9, pp. 1454-1469, Sept. 2018. file
9 Su-Jin Shin, and Il-Chul Moon, "Guided HTM: Hierarchical Topic Model with Dirichlet Forest Priors", IEEE Transactions on Knowledge & Data Engineering. vol. 29 no. 2, p. 330-343, Feb., 2017 file
8 Lee, W.S., Lee, Y.M., Kim, H.Y., and Moon, I.-C., 2016. Bayesian Nonparametric Collaborative Topic Poisson Factorization for Electronic Health Records-Based Phenotyping. IJCAI 2016. pp.2544-2552, New York, USA file
7 Bae, J. W., Bae, S. W., Moon, I. C., & Kim, T. G. (2016). Efficient Flattening Algorithm for Hierarchical and Dynamic Structure Discrete Event Models. ACM Transactions on Modeling and Computer Simulation (TOMACS), 26(4), 25. file
» Bae, J. W., & Moon, I. C. (2016). LDEF Formalism for Agent-Based Model Development. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(6), 793–808. file
5 Lee, W.S., Park, S.R. and Moon, I.-C., 2014. Modeling Multiple Fields of Collective Emotions with Brownian Agent-Based Model. In AAMAS. Paris, France. file
4 Shinjae Yoo, Yiming Yang, Frank Lin, and Il-Chul Moon, Mining Social Networks for Personalized Email Prioritization, ACM SIGKDD Conference, Paris, France, Jun, 28, 2009 file
3 Il-Chul Moon and Kathleen M. Carley, Self-Organizing Social and Spatial Networks under What-if Scenarios, Autonomous Agent and Multi-Agent Systems (AAMAS’07), Honolulu, Hawaii, May 14-18, 2007, pp 127-134 file
2 Yiming Yang, Shinjae Yoo, Frank Lin, and Il-Chul Moon, Personalized Email Prioritization Based on Content and Social Network Analysis, IEEE Intelligent Systems, Special Issue on Social Learning, Vol. 25, Issue 4, pp 12-18, Jul/Aug 2010 file
1 Il-Chul Moon and Kathleen M. Carley, Modeling and Simulation of Terrorist Networks in Social and Geospatial dimensions, IEEE Intelligent Systems, Special Issue on Social Computing, Vol. 22, pp 40-49, Sep/Oct. 2007 file
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